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Background and aims: The effects of metabolic obesity (MO) phenotypes status and their dynamic changes on urologic cancer (UC) is ignored. We aimed to investigate the association between metabolic syndrome (MetS) and MO status at baseline, their dynamic changes and UC risk. Methods: This paper studied 97,897 subjects who were free of cancers at baseline (2006−2007). Individuals were classified into four MO phenotypes by MetS and obesity at baseline. Transitions in MetS and MO status from 2006–2007 to 2008–2009 were considered. The hazard ratios (HRs) and 95% confidence intervals (CIs) for UC were assessed by multifactorial Cox proportional risk regression models. The main limitations of this study are as follows: the ratio of men to women in the cohort is unbalanced; the impacts of MetS and MO on each cancer type (kidney cancer, prostate cancer, bladder cancer) have not been analyzed separately; the transition intervals of MetS and MO phenotypes are relatively short. Results: From baseline (2006–2007) survey to December 31, 2020, during a median follow-up of 14.02 years, 554 cases of UC were diagnosed. Participants with MetS [HRs (95% CI) = 1.26 (1.06–1.49)] and metabolically unhealthy obesity (MUO) [HRs (95% CI) = 1.49 (1.17–1.89)] had significantly higher risk of UC than those with non-MetS and metabolically healthy normal weight (MHN). Transitions in MetS and MO phenotypes over time were studied. Compared with non-MetS to non-MetS, the risks for UC in MetS to MetS [HRs (95% CI) = 1.45 (1.11–1.88)] was increased. Compared with MHN to MHN, both MUO to metabolically healthy obesity (MHO) [HRs (95% CI) = 2.65 (1.43–4.92)] and MUO to MUO [HRs (95% CI) = 1.60 (1.06–2.42)] had significantly higher UC risk. Conclusions: MetS and MUO increased the UC risk at baseline. Transitions of MetS to MetS, MUO to MUO and even MUO to MHO over time significantly increased the risk of UC development. [ABSTRACT FROM AUTHOR]

Intraspecies variations that affect pathogenicity and antifungal resistance traits pose a serious obstacle to efficient therapy of Candida auris infections. Recent reports indicate that mutations determine drug susceptibility and virulence. However, mutations alone cannot fully explain a bewildering variety of phenotypes in clinical isolates from known C. auris clades, suggesting an unprecedented complexity underlying virulence traits and antifungal resistance. Hence, we wish to discuss how phenotypic plasticity promotes morphogenetic switching and how that contributes to intraspecies variations in the human fungal pathogen C. auris. Further, we will also discuss how intraspecies variations and morphogenetic events can impact the progress in molecular mycology research that aims to find better treatments for C. auris infections. Finally, we will present our opinion as to the most relevant questions to be addressed when trying to better understand the pathophysiology of C. auris. [ABSTRACT FROM AUTHOR]

Recent evidence suggests that androgens are a potent driver of growth during late the primary stage of ovarian follicle development in teleosts. We have previously shown that the non-aromatizable androgen, 11-ketotestosterone (11-KT), both advances ovarian follicle growth in vivo and dramatically alters the primary growth ovarian transcriptome in coho salmon. Many of the transcriptomic changes pointed towards 11-KT driving process associated with the transition to a secondary growth phenotype. In the current study, we implanted previtellogenic early secondary growth coho salmon with cholesterol pellets containing 11-KT and performed RNA-Seq on ovarian tissue after 3 days in order to identify alterations to the ovarian transcriptome in early secondary growth. We identified 8,707 contiguous sequences (contigs) that were differentially expressed (DE) between control and 11-KT implanted fish and were able to collapse those to 3,853 gene-level IDs, more than a 3-fold more DE contigs than at the primary growth stage we reported previously. These contigs included genes encoding proteins involved in steroidogenesis, vitellogenin and lipid uptake, follicle stimulating hormone signaling, growth factor signaling, and structural proteins, suggesting androgens continue to promote previtellogenic secondary growth. [ABSTRACT FROM AUTHOR]

Background: Analysis of existing mutations of Angiotensin-I-Converting Enzyme (ACE) led us to hypothesize that the carriers of damaging ACE mutations (accompanied by low ACE levels) could be at risk for the development of late-onset Alzheimer's disease (AD). Methodology/Principal findings: We quantified blood ACE levels in EDTA-containing plasma from 15 patients with 11 different heterozygous ACE mutations and estimated the effects of these mutations on ACE phenotypes, using a set of mAbs to ACE and two ACE substrates. We confirmed prior observations that the relatively frequent Y215C mutation in the N domain of ACE (present in ~1% of the population) is associated with both Alzheimer's disease (AD) and reduced plasma levels of ACE (~50% of controls), indicating that it likely results in a transport-deficient protein. In addition, we identified another 4 mutations in both ACE domains (M118T, C734Y, V992M and V997M) which are also associated with decreased ACE levels in the blood, and, thus, could be putative risk factors for late-onset AD. One of these mutations, C734Y, is likely transport-deficient, while the other mutations appear to influence ACE catalytic properties. The precipitation of mutant M118T by mAb 2D1 and ACE mutant C734Y by mAb 3F10 increased 2-3-fold compared to native ACE, and therefore, these mAbs could be markers of these mutations. Also, we identified a mutation I989T, which is associated with increased ACE levels in the blood. Conclusions/Significance: Conducting a systematic analysis of blood ACE levels in patients with ACE mutations holds promise for identifying individuals with low blood ACE levels. Such individuals may be at increased risk for late-onset AD. The patients with transport-deficient ACE mutations may benefit from therapeutic treatment with a combination of chemical and pharmacological chaperones and proteasome inhibitors, as was demonstrated previously using a cell model of the transport-deficient ACE mutation, Q1069R [Danilov et al, PLoS One, 2010]. [ABSTRACT FROM AUTHOR]

Whole genome sequencing has been an effective tool in the discovery of variants that cause rare diseases. In this study, we determined the suitability of a novel avidity sequencing approach for rare disease applications. We built a sample to results workflow, combining this sequencing technology with standard library preparation kits, analysis workflows, and interpretation tools. We applied the workflow to ten pedigrees with inherited retinal degeneration (IRD) phenotype. Candidate variants of interest identified through whole genome sequencing were further evaluated using segregation analysis in the additional family members. Potentially causal variants in known IRD genes were detected in five of the ten cases. These high confidence variants were found in ABCA4, CERKL, MAK, PEX6 and RDH12 genes associated with retinal degeneration, that could be sufficient to cause pathology. Pending confirmatory clinical evaluation, we observed a 50% diagnostic yield, consistent with previously reported outcomes of IRD patient analysis. The study confirms that avidity sequencing is effective in detection of causal variants when used for whole genome sequencing in rare disease applications. [ABSTRACT FROM AUTHOR]

We evaluated by comparing the performance of three pneumatically-driven bioreactors in the production of L-asparaginase (L-ASNase), an enzyme used to treat leukaemia and lymphoma. A two-step screening process was conducted to detect Cunninghamella spp. strains producing L-ASNase. Cunninghamella echinulata DSM1905 produced the highest levels of L-ASNase during screening assays. Subsequently, fermentations were performed in bubble column (BCR), airlift (ALR), and hybrid fixed-bed airlift (FB-ALR) bioreactors to determine the best upstream bioprocess. Mycelial biomass production was higher in BCR than in ALR and FB-ALR (p ≤ 0.0322). The activity of L-ASNase produced in FB-ALR, in which the fungus grew as a consistent biofilm, was significantly higher (p ≤ 0.022) than that from ALR, which was higher than that of BCR (p = 0.036). The specific activity of ALR and FB-ALR presented no differences (p = 0.073), but it was higher than that of BCR (p ≤ 0.032). In conclusion, C. echinulata DSM1905, grown under the biofilm phenotype, produced the highest levels of L-ASNase, and FB-ALR was the best upstream system for enzyme production. [ABSTRACT FROM AUTHOR]

Transgenic lines engineered through wild type Rhizobium rhizogenes display an altered phenotype known as the Ri phenotype. This phenotype includes a more compact plant habit, which has proved useful to obtain more compact varieties that require less chemical growth regulation. Here, we develop a method for the molecular and cytogenetic characterization of Cape daisy (Osteospermum fruticosum Norl.) Ri lines in order to predict segregation of pRi T-DNA genes. Analysis of copy number variation (CNV) by means of digital PCR indicated large variation in the copy number of the inserted root oncogenic loci (rol) genes, ranging from 1 to more than 15 copies. In addition, up to 9 copies of the auxin biosynthesis genes (aux) were present in a single Ri line. Visualization of pRiA4 and pRi1724 rol and aux insertion in 4 Ri lines was performed through Fluorescence In Situ Hybridization. The number of rol integrated loci varied from 1 to 3 loci. In contrast, the different TR-gene copies were confined to a single locus which consistently co-localized with a TL locus, this was demonstrated for the first time. Based on CNV and FISH a single Ri line, harboring 7 pRi1724 rol gene copies dispersed over 3 integration loci, was selected for breeding. Copy number segregation in R1 progeny of 2, 3, 4 and 5 pRi1724 copies was confirmed, indicating that the evaluation of the breeding value of first generation Ri lines is possible through CNV and FISH. [ABSTRACT FROM AUTHOR]

An understanding of human brain individuality requires the integration of data on brain organization across people and brain regions, molecular and systems scales, as well as healthy and clinical states. Here, we help advance this understanding by leveraging methods from computational genomics to integrate large-scale genomic, transcriptomic, neuroimaging, and electronic-health record data sets. We estimated genetically regulated gene expression (gr-expression) of 18,647 genes, across 10 cortical and subcortical regions of 45,549 people from the UK Biobank. First, we showed that patterns of estimated gr-expression reflect known genetic–ancestry relationships, regional identities, as well as inter-regional correlation structure of directly assayed gene expression. Second, we performed transcriptome-wide association studies (TWAS) to discover 1,065 associations between individual variation in gr-expression and gray-matter volumes across people and brain regions. We benchmarked these associations against results from genome-wide association studies (GWAS) of the same sample and found hundreds of novel associations relative to these GWAS. Third, we integrated our results with clinical associations of gr-expression from the Vanderbilt Biobank. This integration allowed us to link genes, via gr-expression, to neuroimaging and clinical phenotypes. Fourth, we identified associations of polygenic gr-expression with structural and functional MRI phenotypes in the Human Connectome Project (HCP), a small neuroimaging-genomic data set with high-quality functional imaging data. Finally, we showed that estimates of gr-expression and magnitudes of TWAS were generally replicable and that the p-values of TWAS were replicable in large samples. Collectively, our results provide a powerful new resource for integrating gr-expression with population genetics of brain organization and disease. Integrating neuroimaging and molecular brain data across people and brain regions and states can help to understand human brain individuality. This study presents a resource that uses computational genomics to estimate genetically regulated components of gene expression and infer associations of this expression with neuroimaging and clinical phenotypes. [ABSTRACT FROM AUTHOR]

Nirmatrelvir was the first protease inhibitor specifically developed against the SARS-CoV-2 main protease (3CLpro/Mpro) and licensed for clinical use. As SARS-CoV-2 continues to spread, variants resistant to nirmatrelvir and other currently available treatments are likely to arise. This study aimed to identify and characterize mutations that confer resistance to nirmatrelvir. To safely generate Mpro resistance mutations, we passaged a previously developed, chimeric vesicular stomatitis virus (VSV-Mpro) with increasing, yet suboptimal concentrations of nirmatrelvir. Using Wuhan-1 and Omicron Mpro variants, we selected a large set of mutants. Some mutations are frequently present in GISAID, suggesting their relevance in SARS-CoV-2. The resistance phenotype of a subset of mutations was characterized against clinically available protease inhibitors (nirmatrelvir and ensitrelvir) with cell-based, biochemical and SARS-CoV-2 replicon assays. Moreover, we showed the putative molecular mechanism of resistance based on in silico molecular modelling. These findings have implications on the development of future generation Mpro inhibitors, will help to understand SARS-CoV-2 protease inhibitor resistance mechanisms and show the relevance of specific mutations, thereby informing treatment decisions. Author summary: Studying dangerous viruses comes with risks and strict safety requirements. This is also true when new medications against viruses are developed and their effectiveness over time has to be tested. Unfortunately, viruses are quick to mutate and become resistant against almost any new medication. Ideally, this information is available before the medication is widely available. Then, when resistant viruses arise, patient caretakers can switch to other available treatments. However, to study the development of resistance with dangerous viruses is considered as 'gain-of-function' research, which is highly controversial and experiments have to be performed with high biological containment to prevent biosafety breaches. To facilitate studying the development of resistance and circumvent gain-of-function research of dangerous viruses, we describe a new, safe method. With this method, we can generate resistance data without using the actual virus, namely SARS-CoV-2 (alias 'Corona'). We provide resistance data against two clinically used antiviral medications that are relevant for the treatment of SARS-CoV-2. [ABSTRACT FROM AUTHOR]

Mutations in the presenilin (PS) genes are a predominant cause of familial Alzheimer's disease (fAD). An ortholog of PS in the genetic model organism Caenorhabditis elegans (C. elegans) is sel-12. Mutations in the presenilin genes are commonly thought to lead to fAD by upregulating the expression of amyloid beta (Aβ), however this hypothesis has been challenged by recent evidence. As C. elegans lack amyloid beta (Aβ), the goal of this work was to examine Aβ-independent effects of mutations in sel-12 and PS1/PS2 on behaviour and sensory neuron morphology across the lifespan in a C. elegans model. Olfactory chemotaxis experiments were conducted on sel-12(ok2078) loss-of-function mutant worms. Adult sel-12 mutant worms showed significantly lower levels of chemotaxis to odorants compared to wild-type worms throughout their lifespan, and this deficit increased with age. The chemotaxis phenotype in sel-12 mutant worms is rescued by transgenic over-expression of human wild-type PS1, but not the classic fAD-associated variant PS1C410Y, when expression was driven by either the endogenous sel-12 promoter (Psel-12), a pan-neuronal promoter (Primb-1), or by a promoter whose primary expression was in the sensory neurons responsible for the chemotaxis behavior (Psra-6, Podr-10). The behavioural phenotype was also rescued by over-expressing an atypical fAD-linked mutation in PS1 (PS1ΔS169) that has been reported to leave the Notch pathway intact. An examination of the morphology of polymodal nociceptive (ASH) neurons responsible for the chemotaxis behavior also showed increased neurodegeneration over time in sel-12 mutant worms that could be rescued by the same transgenes that rescued the behaviour, demonstrating a parallel with the observed behavioral deficits. Thus, we report an Aβ-independent neurodegeneration in C. elegans that was rescued by cell specific over-expression of wild-type human presenilin. [ABSTRACT FROM AUTHOR]

Cytoplasmic poly(A)-binding protein (PABPC; Pab1 in yeast) is thought to be involved in multiple steps of post-transcriptional control, including translation initiation, translation termination, and mRNA decay. To understand both the direct and indirect roles of PABPC in more detail, we have employed mass spectrometry to assess the abundance of the components of the yeast proteome, as well as RNA-Seq and Ribo-Seq to analyze changes in the abundance and translation of the yeast transcriptome, in cells lacking the PAB1 gene. We find that pab1Δ cells manifest drastic changes in the proteome and transcriptome, as well as defects in translation initiation and termination. Defects in translation initiation and the stabilization of specific classes of mRNAs in pab1Δ cells appear to be partly indirect consequences of reduced levels of specific initiation factors, decapping activators, and components of the deadenylation complex in addition to the general loss of Pab1's direct role in these processes. Cells devoid of Pab1 also manifested a nonsense codon readthrough phenotype indicative of a defect in translation termination. Collectively, our results indicate that, unlike the loss of simpler regulatory proteins, elimination of cellular Pab1 is profoundly pleiotropic and disruptive to numerous aspects of post-transcriptional regulation. Author summary: Many human diseases are caused by having too much or too little of certain cellular proteins. The amount of an individual protein is influenced by the level of its messenger mRNA (mRNA) and the efficiency of translation of the mRNA into a polypeptide chain by the ribosomes. Cytoplasmic poly(A)-binding protein (PABPC) plays numerous roles in the regulation of this multi-staged process, but understanding its specific role has been challenging because it is sometimes unclear whether experimental results are related to PABPC's direct role in a specific biochemical process or to indirect effects of its other roles, leading to conflicting models of PABPC's functions between studies. Here, we characterized defects in different stages of protein synthesis in response to loss of PABPC in yeast cells by measuring whole-cell levels of mRNAs, ribosome-associated mRNAs, and proteins. We demonstrated that defects in most steps of protein synthesis other than the last can be explained by reduced levels of mRNAs that code for proteins important for that step in addition to loss of PABPC's direct role on that step. Our data and analyses serve as resources aiding interpretation of experiments in which PABPC levels have been manipulated and generally point to the resulting complexity of such manipulations. [ABSTRACT FROM AUTHOR]

Clostridioides difficile is a pathogen whose transmission relies on the formation of dormant endospores. Spores are highly resilient forms of bacteria that resist environmental and chemical insults. In recent work, we found that C. difficile SspA and SspB, two small acid-soluble proteins (SASPs), protect spores from UV damage and, interestingly, are necessary for the formation of mature spores. Here, we build upon this finding and show that C. difficile sspA and sspB are required for the formation of the spore cortex layer. Moreover, using an EMS mutagenesis selection strategy, we identified mutations that suppressed the defect in sporulation of C. difficile SASP mutants. Many of these strains contained mutations in CDR20291_0714 (spoIVB2) revealing a connection between the SpoIVB2 protease and the SASPs in the sporulation pathway. This work builds upon the hypothesis that the small acid-soluble proteins can regulate gene expression. Author summary: In prior work, we found that the Clostridioides difficile small acid-soluble proteins, SspA and SspB, are important for the UV resistance that is characteristic of dormant spores (as found in many other spore-forming bacteria). Surprisingly, we also found that the combinatorial deletion of sspA and sspB led to a block in the ability of C. difficile to form dormant spores, a phenotype not observed in other sporulating bacteria. Here, we build upon this work and find that this block can be overcome by mutations in spoIVB2 –σF-regulated protease. Our data suggest that the σG-regulated SspA and SspB directly or indirectly activate spoIVB2 expression during late stages of sporulation and that the identified spoIVB2 alleles overcome the absence of sspA and sspB by increasing spoIVB2 translation efficiency and, thus, abundance during late stages of sporulation. Our data build upon the hypothesis that small acid-soluble proteins can regulate gene expression and indicate that other spore-forming bacteria may have unidentified targets that these proteins may regulate during the sporulation process. [ABSTRACT FROM AUTHOR]

Single-cell RNA sequencing (scRNA-seq) has emerged as a versatile tool in biology, enabling comprehensive genomic-level characterization of individual cells. Currently, most scRNA-seq methods generate barcoded cDNAs by capturing the polyA tails of mRNAs, which exclude many non-coding RNAs (ncRNAs), especially those transcribed by RNA polymerase III (Pol III). Although previously thought to be expressed constitutively, Pol III-transcribed ncRNAs are expressed variably in healthy and disease states and play important roles therein, necessitating their profiling at the single-cell level. In this study, we developed a measurement protocol for nc886 as a model case and initial step for scRNA-seq for Pol III-transcribed ncRNAs. Specifically, we spiked in an oligo-tagged nc886-specific primer during the polyA tail capture process for the 5'scRNA-seq. We then produced sequencing libraries for standard 5' gene expression and oligo-tagged nc886 separately, to accommodate different cDNA sizes and ensure undisturbed transcriptome analysis. We applied this protocol in three cell lines that express high, low, and zero levels of nc886. Our results show that the identification of oligo tags exhibited limited target specificity, and sequencing reads of nc886 enabled the correction of non-specific priming. These findings suggest that gene-specific primers (GSPs) can be employed to capture RNAs lacking a polyA tail, with subsequent sequence verification ensuring accurate gene expression counting. Moreover, we embarked on an analysis of differentially expressed genes in cell line sub-clusters with differential nc886 expression, demonstrating variations in gene expression phenotypes. Collectively, the primer spike-in strategy allows combined analysis of ncRNAs and gene expression phenotype. [ABSTRACT FROM AUTHOR]

Chemical mutagenesis-driven forward genetic screens are pivotal in unveiling gene functions, yet identifying causal mutations behind phenotypes remains laborious, hindering their high-throughput application. Here, we reveal a non-uniform mutation rate caused by Ethyl Methane Sulfonate (EMS) mutagenesis in the C. elegans genome, indicating that mutation frequency is influenced by proximate sequence context and chromatin status. Leveraging these factors, we developed a machine learning enhanced pipeline to create a comprehensive EMS mutagenesis probability map for the C. elegans genome. This map operates on the principle that causative mutations are enriched in genetic screens targeting specific phenotypes among random mutations. Applying this map to Whole Genome Sequencing (WGS) data of genetic suppressors that rescue a C. elegans ciliary kinesin mutant, we successfully pinpointed causal mutations without generating recombinant inbred lines. This method can be adapted in other species, offering a scalable approach for identifying causal genes and revitalizing the effectiveness of forward genetic screens. Author summary: Exploring gene functions through chemical mutagenesis-driven genetic screens is pivotal, yet the cumbersome task of identifying causative mutations remains a bottleneck, limiting their high-throughput potential. In this investigation, we uncovered a non-uniform mutation pattern induced by Ethyl Methane Sulfonate (EMS) mutagenesis in the C. elegans genome, highlighting the influence of proximate sequence context and chromatin status on mutation frequency. Leveraging these insights, we engineered a machine learning enhanced pipeline to construct a comprehensive EMS mutagenesis probability map for the C. elegans genome. This map operates on the principle that causative mutations are selectively enriched in genetic screens targeting specific phenotypes amid the backdrop of random mutations. Applying this mapping tool to Whole Genome Sequencing (WGS) data derived from genetic suppressors rescuing a C. elegans ciliary kinesin mutant, we achieved precise identification of causal mutations without resorting to the conventional generation of recombinant inbred lines. Our work not only advances understanding of mutation dynamics but also revitalizes the efficacy of forward genetic screens, contributing to the refinement of genetic exploration methodologies with implications for various organisms. [ABSTRACT FROM AUTHOR]

Many of the most highly conserved elements in the human genome are "poison exons," alternatively spliced exons that contain premature termination codons and permit post-transcriptional regulation of mRNA abundance through induction of nonsense-mediated mRNA decay (NMD). Poison exons are widely assumed to be highly conserved due to their presumed importance for organismal fitness, but this functional importance has never been tested in the context of a whole organism. Here, we report that a poison exon in Smndc1 is conserved across mammals and plants and plays a molecular autoregulatory function in both kingdoms. We generated mouse and A. thaliana models lacking this poison exon to find its loss leads to deregulation of SMNDC1 protein levels, pervasive alterations in mRNA processing, and organismal size restriction. Together, these models demonstrate the importance of poison exons for both molecular and organismal phenotypes that likely explain their extraordinary conservation. Author summary: Poison exons are highly conserved elements in the human genome and are known for their roles in regulating mRNA abundance. Despite their assumed importance for organismal fitness, their functional significance has not been tested in whole organisms. Our study focuses on a poison exon in the Smndc1 gene. We discovered that this poison exon is conserved between mammals and plants and sought to test its functional importance. We generated mouse and plant models lacking this specific poison exon. The loss of this exon led to dysregulated SMNDC1 protein levels and widespread disruptions in RNA processing. These molecular changes resulted in a noticeable reduction in organismal size, underscoring the physiological impact of poison exon loss. Our findings demonstrate that poison exons are crucial for maintaining proper protein levels and mRNA processing homeostasis, which may partially explain their remarkable evolutionary conservation. This study highlights the importance of poison exons in both molecular regulation and overall organismal health, providing insights into their conservation across diverse species. [ABSTRACT FROM AUTHOR]

Pseudomonas aeruginosa is an opportunist bacterium that causes acute and chronic infections. During acute infections, the type III secretion system (T3SS) plays a pivotal role in allowing the bacteria to translocate effectors such as ExoS, ExoT, and ExoY into host cells for colonization. Previous research on the involvement of quorum sensing systems Las and Rhl in controlling the T3SS gene expression produced ambiguous results. In this study, we determined the role of the Las and Rhl systems and the PqsE protein on T3SS expression. Our results show that in the wild-type PAO1 strain, the deletion of lasR or pqsE do not affect the secretion of ExoS. However, rhlI inactivation increases the expression of T3SS genes. In contrast to the rhlI deletion, rhlR inactivation decreases both T3SS genes expression and ExoS secreted protein levels, and this phenotype is restored when this mutant is complemented with the exsA gene, which codes for the master regulator of the T3SS. Additionally, cytotoxicity is affected in the rhlR mutant strain compared with its PAO1 parental strain. Overall, our results indicate that neither the Las system nor PqsE are involved in regulating the T3SS. Moreover, the Rhl system components have opposite effects, RhlI participates in negatively controlling the T3SS expression, while RhlR does it in a positive way, and this regulation is independent of C4 or PqsE. Finally, we show that rhlR, rhlI, or pqsE inactivation abolished pyocyanin production in T3SS-induction conditions. The ability of RhlR to act as a positive T3SS regulator in the absence of its cognate autoinducer and PqsE shows that it is a versatile regulator that controls different virulence traits allowing P. aeruginosa to compete for a niche. [ABSTRACT FROM AUTHOR]

The zinc finger and BTB domain-containing 11 gene (zbtb11) is expressed in the Xenopus anterior neuroectoderm, but the molecular nature of the Zbtb11 protein during embryonic development remains to be elucidated. Here, we show the role of Zbtb11 in anterior patterning of the neuroectoderm and the cooperative action with the transcription factor Otx2. Both overexpression and knockdown of zbtb11 caused similar phenotypes: expanded expression of the posterior gene gbx2 in the neural plate, and later microcephaly with reduced eyes, suggesting that a proper level of zbtb11 expression is necessary for normal patterning of the neuroectoderm, including eye formation. Co-immunoprecipitation assays showed that Zbtb11 formed a complex with itself and with a phosphomimetic and repressive form of Otx2, suggesting that Zbtb11 forms a dimer or oligomer and interacts with Otx2 in a phosphorylation-dependent manner. Reporter analysis further showed that Zbtb11 enhanced the activity of the phosphomimetic Otx2 to repress a silencer element of the posterior gene meis3. These data suggest that Zbtb11 coordinates with phosphorylated Otx2 to specify the anterior neuroectoderm by repressing posterior genes. [ABSTRACT FROM AUTHOR]

Brazil is the largest global producer of sugarcane and plays a significant role—supplier of sugar and bioethanol. However, diseases such as brown and orange rust cause substantial yield reductions and economic losses, due decrease photosynthesis and biomass in susceptible cultivars. Molecular markers associated with resistance genes, such as Bru1 (brown rust) and G1 (orange rust), could aid in predicting resistant genotypes. In this study, we sought to associate the phenotypic response of 300 sugarcane accessions with the genotypic response of Bru1 and G1 markers. The field trials were conducted in a randomized block design, and five six-month-old plants per plot were evaluated under natural disease conditions. Genotypic information about the presence or absence of Bru1 (haplotype 1) and G1 gene was obtained after extraction of genomic DNA and conventional PCR. Of the total accessions evaluated, 60.3% (181) showed resistance to brown rust in the field, and of these, 70.7% (128) had the Bru1 gene present. Considering the field-resistant accessions obtained from Brazilian breeding programs (116), the Bru1 was present in 77,6% of these accessions. While alternative resistance sources may exist, Bru1 likely confers enduring genetic resistance in current Brazilian cultivars. Regarding the phenotypic reaction to orange rust, the majority of accessions, 96.3% (288), were field resistant, and of these, 52.7% (152) carried the G1 marker. Although less efficient for predicting resistance when compared to Bru1, the G1 marker could be part of a quantitative approach when new orange rust resistance genes are described. Therefore, these findings showed the importance of Bru1 molecular markers for the early selection of resistant genotypes to brown rust by genetic breeding programs. [ABSTRACT FROM AUTHOR]

Given the recent global surge in Legionnaires' disease cases, the monitoring of Legionella pneumophila becomes increasingly crucial. Epidemiological cases often stem from local outbreaks rather than widespread dissemination, emphasizing the need to study the characteristics of this pathogen at a local level. This study focuses on isolates of L. pneumophila in the Italian region of Friuli Venezia Giulia to assess specific genotype and phenotype distribution over time and space. To this end, a total of 127 L. pneumophila strains isolated between 2005 and 2017 within national surveillance programs were analysed. Rep-PCR, RAPD, and Sau-PCR were used for genotypic characterization, while phenotypic characterization was conducted through fatty acids analysis. RAPD and Sau-PCR effectively assessed genetic characteristics, identifying different profiles for the isolates and excluding the presence of clones. Although Sau-PCR is rarely used to analyse this pathogen, it emerged as the most discriminatory technique. Phenotypically, hierarchical cluster analysis categorized strains into three groups based on varying membrane fatty acid percentages. However, both phenotypic and genotypic analyses revealed a ubiquitous profile distribution at a regional level. These results suggest an absence of correlations between strain profiles, geographical location, and isolation time, indicating instead high variability and strain dissemination within this region. [ABSTRACT FROM AUTHOR]

Docetaxel (Doc) plays a crucial role in clinical antineoplastic practice. However, it is continuously documented that tumors frequently develop chemoresistance and relapse, which may be related to polyploid giant cancer cells (PGCCs). The aim of this study was investigate the formation mechanism and biological behavior of PGCCs induced by Doc. Ovarian cancer cells were treated with Doc, and then the effect of Doc on cellular viability was evaluated by MTT assay and microscopic imaging analysis. The biological properties of PGCCs were further evaluated by Hoechst 33342 staining, cell cycle and DNA content assay, DNA damage response (DDR) signaling detection, β-galactosidase staining, mitochondrial membrane potential detection, and reverse transcription-quantitative polymerase chain reaction. The results indicated that Doc reduced cellular viability; however, many cells were still alive, and were giant and polyploid. Doc increased the proportion of cells stayed in the G2/M phase and reduced the number of cells. In addition, the expression of γ-H2A.X was constantly increased after Doc treatment. PGCCs showed senescence-associated β-galactosidase activity and an increase in the monomeric form of JC-1. The mRNA level of octamer-binding transcription factor 4 (OCT4) and krüppel-like factor 4 (KLF4) was significantly increased in PGCCs. Taken together, our results suggest that Doc induces G2/M cell cycle arrest, inhibits the proliferation and activates persistent DDR signaling to promote the formation of PGCCs. Importantly, PGCCs exhibit a senescence phenotype and express stem cell markers. [ABSTRACT FROM AUTHOR]

Glial cells such as astrocytes can modulate neuronal signaling. Astrocytes can also acquire a reactive phenotype that correlates with cognitive impairments in brain diseases. A study in PLOS Biology shows that prolonged activation of astrocytes can trigger both cognitive impairments and a reactive astrocyte phenotype. Astrocytes can modulate neuronal activity and also acquire a reactive phenotype that correlates with cognitive impairments in brain diseases. A study in PLOS Biology shows that prolonged activation of astrocytes can trigger both cognitive impairments and a reactive astrocyte phenotype. [ABSTRACT FROM AUTHOR]

Filamentous cell growth is a vital property of fungal pathogens. The mechanisms of filamentation in the emerging multidrug-resistant fungal pathogen Candida auris are poorly understood. Here, we show that exposure of C. auris to glycerol triggers a rod-like filamentation-competent (RL-FC) phenotype, which forms elongated filamentous cells after a prolonged culture period. Whole-genome sequencing analysis reveals that all RL-FC isolates harbor a mutation in the C2H2 zinc finger transcription factor-encoding gene GFC1 (Gfc1 variants). Deletion of GFC1 leads to an RL-FC phenotype similar to that observed in Gfc1 variants. We further demonstrate that GFC1 mutation causes enhanced fatty acid β-oxidation metabolism and thereby promotes RL-FC/filamentous growth. This regulation is achieved through a Multiple Carbon source Utilizer (Mcu1)-dependent mechanism. Interestingly, both the evolved RL-FC isolates and the gfc1Δ mutant exhibit an enhanced ability to colonize the skin. Our results reveal that glycerol-mediated GFC1 mutations are beneficial during C. auris skin colonization and infection. Author summary: Candida auris is an emerging multidrug-resistant fungal pathogen that has rapidly spread worldwide in the past decade. This fungus can manifest filamentous morphology under certain conditions, such as passage through a mammalian host. Here, we demonstrate that exposure of C. auris to glycerol triggers a rod-like filamentation-competent (RL-FC) phenotype, resulting in elongated filamentous cells post a prolonged cultivation. Whole-genome sequencing analysis indicates that mutation of a C2H2 zinc finger transcription factor-encoding gene GFC1 is responsible for the generation of RL-FC/filamentous phenotype and enhances ability of skin colonization. We further substantiate that Multiple Carbon source Utilizer (Mcu1)-mediated fatty acid β-oxidation metabolism contributes to Gfc1-suppressed filamentous growth. Our findings link a single gene mutation to metabolic adaptation and acquisition of filamentous competence in C. auris, shedding light on how adaptive traits emerge in pathogens to enhance colonization and infection of the host. [ABSTRACT FROM AUTHOR]

MIR125B, particularly its 5p strand, is apparently involved in multiple cellular processes, including osteoblastogenesis and osteoclastogenesis. Given that MIR125B is transcribed from the loci Mir125b1 and Mir125b2, three mature transcripts (MIR125B-5p, MIR125B1-3p, and MIR125B2-3p) are generated (MIR125B-5p is common to both); however, their expression profiles and roles in the bones remain poorly understood. Both primary and mature MIR125B transcripts were differentially expressed in various organs, tissues, and cells, and their expression patterns did not necessarily correlate in wild-type (WT) mice. We generated Mir125b2 knockout (KO) mice to examine the contribution of Mir125b2 to MIR125B expression profiles and bone phenotypes. Mir125b2 KO mice were born and grew normally without any changes in bone parameters. Interestingly, in WT and Mir125b2 KO, MIR125B-5p was abundant in the calvaria and bone marrow stromal cells. These results indicate that the genetic ablation of Mir125b2 does not impinge on the bones of mice, attracting greater attention to MIR125B-5p derived from Mir125b1. Future studies should investigate the conditional deletion of Mir125b1 and both Mir125b1 and Mir125b2 in mice. [ABSTRACT FROM AUTHOR]

Quorum sensing (QS) is a regulatory mechanism used by bacteria to coordinate group behavior in response to high cell densities. During QS, cells monitor the concentration of external signals, known as autoinducers, as a proxy for cell density. QS often involves positive feedback loops, leading to the upregulation of genes associated with QS signal production and detection. This results in distinct steady-state concentrations of QS-related molecules in QS-ON and QS-OFF states. Due to the slow decay rates of biomolecules such as proteins, even after removal of the initial stimuli, cells can retain elevated levels of QS-associated biomolecules for extended periods of time. This persistence of biomolecules after the removal of the initial stimuli has the potential to impact the response to future stimuli, indicating a memory of past exposure. This phenomenon, which is a consequence of the carry-over of biomolecules rather than genetic inheritance, is known as "phenotypic" memory. This theoretical study aims to investigate the presence of phenotypic memory in QS and the conditions that influence this memory. Numerical simulations based on ordinary differential equations and analytical modeling were used to study gene expression in response to sudden changes in cell density and extracellular signal concentrations. The model examined the effect of various cellular parameters on the strength of QS memory and the impact on gene regulatory dynamics. The findings revealed that QS memory has a transient effect on the expression of QS-responsive genes. These consequences of QS memory depend strongly on how cell density was perturbed, as well as various cellular parameters, including the Fold Change in the expression of QS-regulated genes, the autoinducer synthesis rate, the autoinducer threshold required for activation, and the cell growth rate. Author summary: Bacteria use a mechanism known as quorum sensing (QS) to collaborate when their numbers are high. In various QS systems, cells detect specific signals that trigger certain genes, resulting in increased production of certain molecules in response to these signals. Interestingly, these molecules can linger even after the initial signal is gone, which can resemble a form of "memory." Our theoretical study focuses on exploring this memory and the factors that influence it. To do this, we used simulations and models to examine how history of exposure to signals can affect the future response, when signals are removed, and cell density is reduced. We found that the prior exposure to signals can influence how bacteria respond in the future, but this effect occurs under specific conditions. This research contributes to our understanding of quorum sensing and how bacteria adapt to environmental changes. [ABSTRACT FROM AUTHOR]

Background: Phenome-Wide Association study (PheWAS) is a powerful tool designed to systematically screen clinical observations derived from medical records (phenotypes) for association with a variable of interest. Despite their usefulness, no systematic screening of phenotypes associated with Staphylococcusaureusinfections (SAIs) has been done leaving potential novel risk factors or complications undiscovered. Method and cohorts: We tailored the PheWAS approach into a two-stage screening procedure to identify novel phenotypes correlating with SAIs. The first stage screened for co-occurrence of SAIs with other phenotypes within medical records. In the second stage, significant findings were examined for the correlations between their age of onset with that of SAIs. The PheWAS was implemented using the medical records of 754,401 patients from the Marshfield Clinic Health System. Any novel associations discovered were subsequently validated using datasets from TriNetX and All of Us, encompassing 109,884,571 and 118,538 patients respectively. Results: Forty-one phenotypes met the significance criteria of a p-value < 3.64e-5 and odds ratios of > 5. Out of these, we classified 23 associations either as risk factors or as complications of SAIs. Three novel associations were discovered and classified either as a risk (long-term use of aspirin) or complications (iron deficiency anemia and anemia of chronic disease). All novel associations were replicated in the TriNetX cohort. In the All of Us cohort, anemia of chronic disease was replicated according to our significance criteria. Conclusions: The PheWAS of SAIs expands our understanding of SAIs interacting phenotypes. Additionally, the novel two-stage PheWAS approach developed in this study can be applied to examine other disease-disease interactions of interest. Due to the possibility of bias inherent in observational data, the findings of this study require further investigation. [ABSTRACT FROM AUTHOR]

We show here that in the fungus Sordaria macrospora, the meiosis-specific HORMA-domain protein Hop1 is not essential for the basic early events of chromosome axis development, recombination initiation, or recombination-mediated homolog coalignment/pairing. In striking contrast, Hop1 plays a critical role at the leptotene/zygotene transition which is defined by transition from pairing to synaptonemal complex (SC) formation. During this transition, Hop1 is required for maintenance of normal axis structure, formation of SC from telomere to telomere, and development of recombination foci. These hop1Δ mutant defects are DSB dependent and require Sme4/Zip1-mediated progression of the interhomolog interaction program, potentially via a pre-SC role. The same phenotype occurs not only in hop1Δ but also in absence of the cohesin Rec8 and in spo76-1, a non-null mutant of cohesin-associated Spo76/Pds5. Thus, Hop1 and cohesins collaborate at this crucial step of meiotic prophase. In addition, analysis of 4 non-null mutants that lack this transition defect reveals that Hop1 also plays important roles in modulation of axis length, homolog-axis juxtaposition, interlock resolution, and spreading of the crossover interference signal. Finally, unexpected variations in crossover density point to the existence of effects that both enhance and limit crossover formation. Links to previously described roles of the protein in other organisms are discussed. Hop1 has been previously shown to display diverse meiotic functions in different organisms. This study identifies and characterizes the functions of Hop1 in the fungus Sordaria macrospora and shows that it plays a crucial role during the leptotene/zygotene transition and formation of the synaptonemal complex during meiotic prophase. [ABSTRACT FROM AUTHOR]

In this study, we employed various machine learning models to predict metabolic phenotypes, focusing on thyroid function, using a dataset from the National Health and Nutrition Examination Survey (NHANES) from 2007 to 2012. Our analysis utilized laboratory parameters relevant to thyroid function or metabolic dysregulation in addition to demographic features, aiming to uncover potential associations between thyroid function and metabolic phenotypes by various machine learning methods. Multinomial Logistic Regression performed best to identify the relationship between thyroid function and metabolic phenotypes, achieving an area under receiver operating characteristic curve (AUROC) of 0.818, followed closely by Neural Network (AUROC: 0.814). Following the above, the performance of Random Forest, Boosted Trees, and K Nearest Neighbors was inferior to the first two methods (AUROC 0.811, 0.811, and 0.786, respectively). In Random Forest, homeostatic model assessment for insulin resistance, serum uric acid, serum albumin, gamma glutamyl transferase, and triiodothyronine/thyroxine ratio were positioned in the upper ranks of variable importance. These results highlight the potential of machine learning in understanding complex relationships in health data. However, it's important to note that model performance may vary depending on data characteristics and specific requirements. Furthermore, we emphasize the significance of accounting for sampling weights in complex survey data analysis and the potential benefits of incorporating additional variables to enhance model accuracy and insights. Future research can explore advanced methodologies combining machine learning, sample weights, and expanded variable sets to further advance survey data analysis. [ABSTRACT FROM AUTHOR]

The presence of SNPs in genes related to DNA damage repair in M. tuberculosis can trigger hypermutagenic phenotypes with a higher probability of generating drug resistance. The aim of this research was to compare the presence of SNPs in genes related to DNA damage repair between sensitive and DR isolates, as well as to describe the dynamics in the presence of SNPs in M. tuberculosis isolated from recently diagnosed TB patients of the state of Veracruz, Mexico. The presence of SNPs in the coding regions of 65 genes related to DNA damage repair was analyzed. Eighty-six isolates from 67 patients from central Veracruz state, Mexico, were sequenced. The results showed several SNPs in 14 genes that were only present in drug-resistant genomes. In addition, by following of 15 patients, it was possible to describe three different dynamics of appearance and evolution of non-synonymous SNPs in genes related to DNA damage repair: 1) constant fixed SNPs, 2) population substitution, and 3) gain of fixed SNPs. Further research is required to discern the biological significance of each of these pathways and their utility as markers of DR or for treatment prognosis. [ABSTRACT FROM AUTHOR]

The plant BEACH-domain protein SPIRRIG (SPI) is involved in regulating cell morphogenesis and salt stress responses in Arabidopsis thaliana, Arabis alpina, and Marchantia polymorpha and was reported to function in the context of two unrelated cellular processes: vesicular trafficking and P-body mediated RNA metabolism. To further explore the molecular function of SPI, we isolated a second-site mutant, specifically rescuing the spi mutant trichome phenotype. The molecular analysis of the corresponding gene revealed a dominant negative mutation in RABE1C, a ras-related small GTP-binding protein that localizes to Golgi. Taken together, our data identified the genetic interaction between RABE1C and SPI, which is beneficial for further dissecting the function of SPI in vesicle trafficking-associated cell morphogenesis. [ABSTRACT FROM AUTHOR]

Wheat varieties show a large diversity of traits and phenotypes. Linking them to genetic variability is essential for shorter and more efficient wheat breeding programs. A growing number of plant molecular information networks provide interlinked interoperable data to support the discovery of gene-phenotype interactions. A large body of scientific literature and observational data obtained in-field and under controlled conditions document wheat breeding experiments. The cross-referencing of this complementary information is essential. Text from databases and scientific publications has been identified early on as a relevant source of information. However, the wide variety of terms used to refer to traits and phenotype values makes it difficult to find and cross-reference the textual information, e.g. simple dictionary lookup methods miss relevant terms. Corpora with manually annotated examples are thus needed to evaluate and train textual information extraction methods. While several corpora contain annotations of human and animal phenotypes, no corpus is available for plant traits. This hinders the evaluation of text mining-based crop knowledge graphs (e.g. AgroLD, KnetMiner, WheatIS-FAIDARE) and limits the ability to train machine learning methods and improve the quality of information. The Triticum aestivum trait Corpus is a new gold standard for traits and phenotypes of wheat. It consists of 528 PubMed references that are fully annotated by trait, phenotype, and species. We address the interoperability challenge of crossing sparse assay data and publications by using the Wheat Trait and Phenotype Ontology to normalize trait mentions and the species taxonomy of the National Center for Biotechnology Information to normalize species. The paper describes the construction of the corpus. A study of the performance of state-of-the-art language models for both named entity recognition and linking tasks trained on the corpus shows that it is suitable for training and evaluation. This corpus is currently the most comprehensive manually annotated corpus for natural language processing studies on crop phenotype information from the literature. [ABSTRACT FROM AUTHOR]

ATP is actively maintained at high concentrations in cancerous tissues, where it promotes a malignant phenotype through P2 receptors. In this study, we first evaluated the effect of extracellular ATP depletion with apyrase in SKOV-3, a cell line derived from metastatic ovarian carcinoma. We observed a decrease in cell migration and an increase in transepithelial electrical resistance and cell markers, suggesting a role in maintaining a mesenchymal phenotype. To identify the P2 receptor that mediated the effects of ATP, we compared the transcript levels of some P2 receptors and found that P2RX7 is three-fold higher in SKOV-3 cells than in a healthy cell line, namely HOSE6-3 (from human ovarian surface epithelium). Through bioinformatic analysis, we identified a higher expression of the P2RX7 transcript in metastatic tissues than in primary tumors; thus, P2X7 seems to be a promising effector for the malignant phenotype. Subsequently, we demonstrated the presence and functionality of the P2X7 receptor in SKOV-3 cells and showed through pharmacological approaches that its activity promotes cell migration and contributes to maintaining a mesenchymal phenotype. P2X7 activation using BzATP increased cell migration and abolished E-cadherin expression. On the other hand, a series of P2X7 receptor antagonists (A438079, BBG and OxATP) decreased cell migration. We used a CRISPR-based knock-out system directed to P2RX7. According to the results of our wound-healing assay, SKOV3-P2X7KO cells lacked receptor-mediated calcium mobilization and decreased migration. Altogether, these data let us propose that P2X7 receptor is a regulator for cancer cell migration and thus a potential drug target. [ABSTRACT FROM AUTHOR]

Malic Enzyme 1 (ME1) plays an integral role in fatty acid synthesis and cellular energetics through its production of NADPH and pyruvate. As such, it has been identified as a gene of interest in obesity, type 2 diabetes, and an array of epithelial cancers, with most work being performed in vitro. The current standard model for ME1 loss in vivo is the spontaneous Mod-1 null allele, which produces a canonically inactive form of ME1. Herein, we describe two new genetically engineered mouse models exhibiting ME1 loss at dynamic timepoints. Using murine embryonic stem cells and Flp/FRT and Cre/loxP class switch recombination, we established a germline Me1 knockout model (Me1 KO) and an inducible conditional knockout model (Me1 cKO), activated upon tamoxifen treatment in adulthood. Collectively, neither the Me1 KO nor Me1 cKO models exhibited deleterious phenotype under standard laboratory conditions. Knockout of ME1 was validated by immunohistochemistry and genotype confirmed by PCR. Transmission patterns favor Me1 loss in Me1 KO mice when maternally transmitted to male progeny. Hematological examination of these models through complete blood count and serum chemistry panels revealed no discrepancy with their wild-type counterparts. Orthotopic pancreatic tumors in Me1 cKO mice grow similarly to Me1 expressing mice. Similarly, no behavioral phenotype was observed in Me1 cKO mice when aged for 52 weeks. Histological analysis of several tissues revealed no pathological phenotype. These models provide a more modern approach to ME1 knockout in vivo while opening the door for further study into the role of ME1 loss under more biologically relevant, stressful conditions. [ABSTRACT FROM AUTHOR]

Quantitative trait loci (QTL) denote regions of DNA whose variation is associated with variations in quantitative traits. QTL discovery is a powerful approach to understand how changes in molecular and clinical phenotypes may be related to DNA sequence changes. However, QTL discovery analysis encompasses multiple analytical steps and the processing of multiple input files, which can be laborious, error prone, and hard to reproduce if performed manually. To facilitate and automate large-scale QTL analysis, we developed the yQTL Pipeline, where the 'y' indicates the dependent quantitative variable being modeled. Prior to the association test, the pipeline supports the calculation or the direct input of pre-defined genome-wide principal components and genetic relationship matrix when applicable. User-specified covariates can also be provided. Depending on whether familial relatedness exists among the subjects, genome-wide association tests will be performed using either a linear mixed-effect model or a linear model. The options to run an ANOVA model or testing the interaction with a covariate are also available. Using the workflow management tool Nextflow, the pipeline parallelizes the analysis steps to optimize run-time and ensure results reproducibility. In addition, a user-friendly R Shiny App is developed to facilitate result visualization. It can generate Manhattan and Miami plots of phenotype traits, genotype-phenotype boxplots, and trait-QTL connection networks. We applied the yQTL Pipeline to analyze metabolomics profiles of blood serum from the New England Centenarians Study (NECS) participants. A total of 9.1M SNPs and 1,052 metabolites across 194 participants were analyzed. Using a p-value cutoff 5e-8, we found 14,983 mQTLs associated with 312 metabolites. The built-in parallelization of our pipeline reduced the run time from ~90 min to ~26 min. Visualization using the R Shiny App revealed multiple mQTLs shared across multiple metabolites. The yQTL Pipeline is available with documentation on GitHub at https://github.com/montilab/yQTLpipeline. [ABSTRACT FROM AUTHOR]

Background: ARDS is a heterogeneous syndrome with distinct clinical phenotypes. Here we investigate whether the presence or absence of large pulmonary ultrasonographic consolidations can categorize COVID-19 ARDS patients requiring mechanical ventilation into distinct clinical phenotypes. Methods: This is a retrospective study performed in a tertiary-level intensive care unit in Israel between April and September 2020. Data collected included lung ultrasound (LUS) findings, respiratory parameters, and treatment interventions. The primary outcome was a composite of three ARDS interventions: prone positioning, high PEEP, or a high dose of inhaled nitric oxide. Results: A total of 128 LUS scans were conducted among 23 patients. The mean age was 65 and about two-thirds were males. 81 scans identified large consolidation and were classified as "C-type", and 47 scans showed multiple B-lines with no or small consolidation and were classified as "B-type". The presence of a "C-type" study had 2.5 times increased chance of receiving the composite primary outcome of advanced ARDS interventions despite similar SOFA scores, Pao2/FiO2 ratio, and markers of disease severity (OR = 2.49, %95CI 1.40–4.44). Conclusion: The presence of a "C-type" profile with LUS consolidation potentially represents a distinct COVID-19 ARDS subphenotype that is more likely to require aggressive ARDS interventions. Further studies are required to validate this phenotype in a larger cohort and determine causality, diagnostic, and treatment responses. [ABSTRACT FROM AUTHOR]

The aquatic perennial herb Sagittaria trifolia L. commonly known as arrowhead, has been utilized in China both as a culinary vegetable and in traditional medicines. Characterizing the phylogenetic relationships and genetic diversity of arrowheads is crucial for improved management, conservation, and efficient utilization of the germplasm resources associated with this species. Herein, we presented the phenotypic traits and genome-wide DNA marker-based analyses of 111 arrowhead accessions, most of which were from China. Cluster analysis revealed that arrowhead could be categorized into two clusters based on 11 phenotypic traits, with Cluster 1 comprising two subclusters. All accessions were clustered into three sub-clusters based primarily on leaf shape and tuber weight. A set of 759,237 high-quality single-nucleotide polymorphisms was identified and used to assess the phylogenetic relationships. Population structure and phylogenetic tree analyses suggested that the accessions could be classified into two major groups, Group I was further subdivided into two subgroups, aligning with the clusters identified through morphological classification. By employing Sagittaria lichuanensis as an outgroup, the rooted tree revealed that the evolutionary relationships within the three groups followed a progression from Group I-1 to Group I-2 and finally to Group II. The landraces were clustered into one group along with the remaining wild accessions. The level of genetic diversity for Group I (π = 0.26) was slightly lower than that which was estimated for Group II (π = 0.29). The lowest pairwise differentiation levels (Fst, 0.008) were obtained from the comparison between groups I-2 and II, indicating that the two groups were the most closely related. This study provides novel insights into germplasm classification, evolutionary relationships, genomics and arrowhead breeding. [ABSTRACT FROM AUTHOR]

Objective: This study aimed to explore the bidirectional causal relationship between periodontal disease-related phenotype (PDRP) and knee osteoarthritis (KOA) in a European population using a two-sample Mendelian Randomization (MR) approach. Methods: We leveraged publicly available GWAS summary statistics for PDRP (n = 975) and KOA (n = 403,124), assessing their roles as both exposures and outcomes. Our comprehensive MR analysis employed various methods, including inverse variance weighting (IVW), weighted median, Egger regression, simple mode, and weighted mode, to enhance the robustness of our findings. To ensure the reliability of our instrumental variables, we implemented a rigorous screening process based on p-values and F-values, utilized Phenoscanner to investigate potential confounders, and conducted sensitivity analyses. Results: Our analysis identified five SNPs associated with PDRP and three SNPs with KOA, all surpassing the genome-wide significance threshold, as instrumental variables. The IVW method demonstrated a significant causal relationship from PDRP to KOA (beta = 0.013, SE = 0.007, P = 0.035), without evidence of directional pleiotropy (MR-Egger regression intercept = 0.021, P = 0.706). No support was found for reverse causality from KOA to PDRP, as further MR analyses yielded non-significant P-values. Additionally, funnel plots and Cochran's Q test detected no significant heterogeneity or directional pleiotropy, confirming the robustness of our results. In multivariate analysis, when considering smoking, alcohol consumption, BMI collectively no direct causal relationship between KOA and PDRP. Conversely, smoking and higher BMI were independently associated with an increased risk of KOA. Conclusion: In conclusion, our analysis revealed no direct causal relationship from KOA to PDRP. However, a causal relationship from PDRP to KOA was observed. Notably, when adjusting for potential confounders like smoking, alcohol intake, and BMI, both the causal connection from PDRP to KOA and the inverse relationship were not substantiated. [ABSTRACT FROM AUTHOR]

To analyze the results of proficiency testing for anti-tuberculosis drug susceptibility testing (DST) in China. Number of laboratory participating the proficiency testing performed DST, and the sensitivity, specificity, reproducibility, and accordance rate were calculated from data of 13 rounds proficiency testing results for DST from 2008 to 2021. A total of 30 and 20 strains of Mycobacterium tuberculosis with known susceptibility results were sent to each laboratory in 2008 to 2019, 2020 and 2021, respectively. The number of participating laboratories ranged from 30 in 2009 to 546 in 2021. L-J DST was the predominant method. The specificity presented relatively higher than sensitivity. Improvement of specificity were observed for all drugs through the years, while sensitivity did not show improvement for amikacin and capreomycin. Accordance rate of pyrazinamide and kanamycin and reproducibility of capreomycin and pyrazinamide were not significantly improved through the years. Most of the participating laboratories significantly improved the quality of their DST through the consecutive rounds of proficiency testing except for second-line injectable drugs and pyrazinamide. The results highlight the importance of developing novel and/or improving existing methods for phenotypic DST for certain drugs. [ABSTRACT FROM AUTHOR]

Comparisons of single-cell RNA sequencing (scRNA-seq) data across species can reveal links between cellular gene expression and the evolution of cell functions, features, and phenotypes. These comparisons evoke evolutionary histories, as depicted by phylogenetic trees, that define relationships between species, genes, and cells. This Essay considers each of these in turn, laying out challenges and solutions derived from a phylogenetic comparative approach and relating these solutions to previously proposed methods for the pairwise alignment of cellular dimensional maps. This Essay contends that species trees, gene trees, cell phylogenies, and cell lineages can all be reconciled as descriptions of the same concept—the tree of cellular life. By integrating phylogenetic approaches into scRNA-seq analyses, challenges for building informed comparisons across species can be overcome, and hypotheses about gene and cell evolution can be robustly tested. Comparisons of single-cell RNA sequencing (scRNA-seq) data across species can reveal links between cellular gene expression and the evolution of cell functions, features, and phenotypes. This Essay contends that, by integrating phylogenetic approaches into scRNA-seq analyses, hypotheses about gene and cell evolution can be robustly tested. [ABSTRACT FROM AUTHOR]

The tempo and mode of adaptation depends on the availability of beneficial alleles. Genetic interactions arising from gene networks can restrict this availability. However, the extent to which networks affect adaptation remains largely unknown. Current models of evolution consider additive genotype-phenotype relationships while often ignoring the contribution of gene interactions to phenotypic variance. In this study, we model a quantitative trait as the product of a simple gene regulatory network, the negative autoregulation motif. Using forward-time genetic simulations, we measure adaptive walks towards a phenotypic optimum in both additive and network models. A key expectation from adaptive walk theory is that the distribution of fitness effects of new beneficial mutations is exponential. We found that both models instead harbored distributions with fewer large-effect beneficial alleles than expected. The network model also had a complex and bimodal distribution of fitness effects among all mutations, with a considerable density at deleterious selection coefficients. This behavior is reminiscent of the cost of complexity, where correlations among traits constrain adaptation. Our results suggest that the interactions emerging from genetic networks can generate complex and multimodal distributions of fitness effects. Author summary: Historically, models of adaptation have typically considered traits as a sum of effects at many genes. Mutations in these genes move a population incrementally closer to an optimum phenotype. However, the genetic basis of traits is often more complex, with interwoven networks of genes creating non-additive effects that might reduce natural selection's ability to steer populations towards optimal trait combinations. In this study, we developed a model that simulates the evolution of a trait as the product of a gene regulatory network. We used this model to compare the effects of the network on adaptation to a typical additive model. We found that mutations in network populations were more likely to drive the population away from an optimum phenotype. We likened this result to the "cost of complexity", where more complicated genetic systems can create constraints on adaptation. Our results suggest that the non-additive interactions emerging from genetic networks might alter the adaptive dynamics predicted under additive models. [ABSTRACT FROM AUTHOR]

The aim of this study was to phenotypically characterize Guraghe and Jimma cattle breeds at the farm level and quantify the relationships between them. Eight morphometric measurements and sixteen morphological traits were recorded for a total of 313 (221 females and 92 males) randomly selected adult cattle from three purposively selected districts. Univariate and multivariate analysis procedures of Statistical Analysis Software (SAS 9.0) were used to analyze the data. Clear morphological and morphometric variations were not observed between the two cattle breeds. All of the studied cattle populations possessed straight-edged ears, a sloppy rump profile, and straight face and back profiles. Moreover, the majority of the studied cattle possess widely spaced curved horns, red-colored uniform body color patterns, and erected small humps located at the cervicothoracic position. In addition to their phenotypic similarities, multivariate analysis also failed to reveal significant differences between the two breeds. These results suggest the inseparable nature of the two cattle breeds. However, such similarities in phenotypic traits between the two cattle breeds do not necessarily indicate genetic similarities. Therefore, further genetic characterization is recommended to quantify the degree of genetic relationship between the breeds. In the meantime, it is recommended to design breed-specific in situ conservation as well as genetic improvement programs that consider cattle breeds as one. Furthermore, an inclusive and uniform breed name that can represent the two cattle populations is obtained from the country's steering committee for indigenous animal genetic resources. [ABSTRACT FROM AUTHOR]

In various biological systems, analyzing how cell behaviors are coordinated over time would enable a deeper understanding of tissue-scale response to physiologic or superphysiologic stimuli. Such data is necessary for establishing both normal tissue function and the sequence of events after injury that lead to chronic disease. However, collecting and analyzing these large datasets presents a challenge—such systems are time-consuming to process, and the overwhelming scale of data makes it difficult to parse overall behaviors. This problem calls for an analysis technique that can quickly provide an overview of the groups present in the entire system and also produce meaningful categorization of cell behaviors. Here, we demonstrate the application of an unsupervised method—the Variational Autoencoder (VAE)—to learn the features of cells in cartilage tissue after impact-induced injury and identify meaningful clusters of chondrocyte behavior. This technique quickly generated new insights into the spatial distribution of specific cell behavior phenotypes and connected specific peracute calcium signaling timeseries with long term cellular outcomes, demonstrating the value of the VAE technique. [ABSTRACT FROM AUTHOR]

Pathway enrichment analysis is a ubiquitous computational biology method to interpret a list of genes (typically derived from the association of large-scale omics data with phenotypes of interest) in terms of higher-level, predefined gene sets that share biological function, chromosomal location, or other common features. Among many tools developed so far, Gene Set Enrichment Analysis (GSEA) stands out as one of the pioneering and most widely used methods. Although originally developed for microarray data, GSEA is nowadays extensively utilized for RNA-seq data analysis. Here, we quantitatively assessed the performance of a variety of GSEA modalities and provide guidance in the practical use of GSEA in RNA-seq experiments. We leveraged harmonized RNA-seq datasets available from The Cancer Genome Atlas (TCGA) in combination with large, curated pathway collections from the Molecular Signatures Database to obtain cancer-type-specific target pathway lists across multiple cancer types. We carried out a detailed analysis of GSEA performance using both gene-set and phenotype permutations combined with four different choices for the Kolmogorov-Smirnov enrichment statistic. Based on our benchmarks, we conclude that the classic/unweighted gene-set permutation approach offered comparable or better sensitivity-vs-specificity tradeoffs across cancer types compared with other, more complex and computationally intensive permutation methods. Finally, we analyzed other large cohorts for thyroid cancer and hepatocellular carcinoma. We utilized a new consensus metric, the Enrichment Evidence Score (EES), which showed a remarkable agreement between pathways identified in TCGA and those from other sources, despite differences in cancer etiology. This finding suggests an EES-based strategy to identify a core set of pathways that may be complemented by an expanded set of pathways for downstream exploratory analysis. This work fills the existing gap in current guidelines and benchmarks for the use of GSEA with RNA-seq data and provides a framework to enable detailed benchmarking of other RNA-seq-based pathway analysis tools. [ABSTRACT FROM AUTHOR]

Castration-resistant prostate cancer (CRPC) is associated with resistance to androgen deprivation therapy, and an increase in the population of neuroendocrine (NE) differentiated cells. It is hypothesized that NE differentiated cells secrete neuropeptides that support androgen-independent tumor growth and induce aggressiveness of adjacent proliferating tumor cells through a paracrine mechanism. The cytochrome b561 (CYB561) gene, which codes for a secretory vesicle transmembrane protein, is constitutively expressed in NE cells and highly expressed in CRPC. CYB561 is involved in the α-amidation-dependent activation of neuropeptides, and contributes to regulating iron metabolism which is often dysregulated in cancer. These findings led us to hypothesize that CYB561 may be a key player in the NE differentiation process that drives the progression and maintenance of the highly aggressive NE phenotype in CRPC. In our study, we found that CYB561 expression is upregulated in metastatic and NE prostate cancer (NEPC) tumors and cell lines compared to normal prostate epithelia, and that its expression is independent of androgen regulation. Knockdown of CYB561 in androgen-deprived LNCaP cells dampened NE differentiation potential and transdifferentiation-induced increase in iron levels. In NEPC PC-3 cells, depletion of CYB561 reduced the secretion of growth-promoting factors, lowered intracellular ferrous iron concentration, and mitigated the highly aggressive nature of these cells in complementary assays for cancer hallmarks. These findings demonstrate the role of CYB561 in facilitating transdifferentiation and maintenance of NE phenotype in CRPC through its involvement in neuropeptide biosynthesis and iron metabolism pathways. [ABSTRACT FROM AUTHOR]

Recessive dystrophic epidermolysis bullosa is a rare genodermatosis caused by a mutation of the Col7a1 gene. The Col7a1 gene codes for collagen type VII protein, a major component of anchoring fibrils. Mutations of the Col7a1 gene can cause aberrant collagen type VII formation, causing an associated lack or absence of anchoring fibrils. This presents clinically as chronic blistering, scarring, and fibrosis, often leading to the development of cutaneous squamous cell carcinoma. Patients also experience persistent pain and pruritus. Pain management and supportive bandaging remain the primary treatment options. The pathology of recessive dystrophic epidermolysis bullosa was first described in the 1980s, and there has since been a multitude of encouraging treatment options developed. However, in vivo research has been hindered by inadequate models of the disease. The various mouse models in existence possess longevity and surface area constraints, or do not adequately model a normal human disease state. In this paper, we describe a novel rat model of recessive dystrophic epidermolysis bullosa that offers an alternative to previous murine models. An 8-base pair deletion was induced in the Col7a1 gene of Lewis rats, which was subsequently found to cause a premature stop codon downstream. Homozygous mutants presented with a fragile and chronically blistered phenotype postnatally. Further histological analysis revealed subepidermal clefting and the absence of anchoring fibrils. The generation of this novel model offers researchers an easily maintained organism that possesses a larger surface area for experimental topical and transfused therapies to be tested, which may provide great utility in the future study of this debilitating disease. [ABSTRACT FROM AUTHOR]

Existing imaging genetics studies have been mostly limited in scope by using imaging-derived phenotypes defined by human experts. Here, leveraging new breakthroughs in self-supervised deep representation learning, we propose a new approach, image-based genome-wide association study (iGWAS), for identifying genetic factors associated with phenotypes discovered from medical images using contrastive learning. Using retinal fundus photos, our model extracts a 128-dimensional vector representing features of the retina as phenotypes. After training the model on 40,000 images from the EyePACS dataset, we generated phenotypes from 130,329 images of 65,629 British White participants in the UK Biobank. We conducted GWAS on these phenotypes and identified 14 loci with genome-wide significance (p<5×10−8 and intersection of hits from left and right eyes). We also did GWAS on the retina color, the average color of the center region of the retinal fundus photos. The GWAS of retina colors identified 34 loci, 7 are overlapping with GWAS of raw image phenotype. Our results establish the feasibility of this new framework of genomic study based on self-supervised phenotyping of medical images. Author summary: Imaging genetics is a research field focused on understanding how genetic variations influence observable traits or diseases that can be visualized through medical imaging. Previous studies in imaging genetics have mostly relied on traits identified by human experts. In this study, we used a self-supervised contrastive learning algorithm that automatically identifies features in fundus images that are unique to each individual yet consistent between their left and right eyes. These features are represented as a set of 128 numbers that can quantitatively describe the characteristics of each individual's fundus images without human labeling bias. We then conducted genome wide association studies (GWAS) to explore the associations between these features and genetic variations using paired fundus images and genetic data from the UK Biobank. Our findings indicate that these features are linked to genetic signals associated with eye measurements, eye diseases, pigmentation, and vessel development. Additionally, we found that GWAS of this set of features identified new genetic signals not detected in GWAS only using retina color. These results establish the feasibility of this self-supervised phenotyping approach for imaging genetics studies. [ABSTRACT FROM AUTHOR]

Joint analysis of multiple correlated phenotypes for genome-wide association studies (GWAS) can identify and interpret pleiotropic loci which are essential to understand pleiotropy in diseases and complex traits. Meanwhile, constructing a network based on associations between phenotypes and genotypes provides a new insight to analyze multiple phenotypes, which can explore whether phenotypes and genotypes might be related to each other at a higher level of cellular and organismal organization. In this paper, we first develop a bipartite signed network by linking phenotypes and genotypes into a Genotype and Phenotype Network (GPN). The GPN can be constructed by a mixture of quantitative and qualitative phenotypes and is applicable to binary phenotypes with extremely unbalanced case-control ratios in large-scale biobank datasets. We then apply a powerful community detection method to partition phenotypes into disjoint network modules based on GPN. Finally, we jointly test the association between multiple phenotypes in a network module and a single nucleotide polymorphism (SNP). Simulations and analyses of 72 complex traits in the UK Biobank show that multiple phenotype association tests based on network modules detected by GPN are much more powerful than those without considering network modules. The newly proposed GPN provides a new insight to investigate the genetic architecture among different types of phenotypes. Multiple phenotypes association studies based on GPN are improved by incorporating the genetic information into the phenotype clustering. Notably, it might broaden the understanding of genetic architecture that exists between diagnoses, genes, and pleiotropy. Author summary: Biological pleiotropy refers to a SNP or gene that has a direct biological influence on more than one phenotypic trait, which can offer significant insights in understanding the complex genotype-phenotype relationships. Network analyses provide an integrative approach to characterize complex genomic associations by linking phenotypes and genotypes into a Genotype and Phenotype Network (GPN). Jointly analyzing multiple phenotypes and incorporating the genetic information into the phenotype clustering may increase the statistical power to discover the cross-phenotype association and pleiotropy. We evaluate our proposed multiple phenotype association tests based on network modules detected by GPN for 72 EHR-derived phenotypes in the diseases of the musculoskeletal system and connective tissue in the UK Biobank. From the post-GWAS analyses, we observe that the test based on GPN can identify more significantly enriched biological pathways than that without considering the network modules. Meanwhile, some of the uniquely identified SNPs by the test based on GPN are also colocalized in the eQTL study of the gene expression in the Muscle Skeletal tissue. [ABSTRACT FROM AUTHOR]

Autism spectrum disorders (ASD) frequently accompany macrocephaly, which often involves hydrocephalic enlargement of brain ventricles. Katnal2 is a microtubule-regulatory protein strongly linked to ASD, but it remains unclear whether Katnal2 knockout (KO) in mice leads to microtubule- and ASD-related molecular, synaptic, brain, and behavioral phenotypes. We found that Katnal2-KO mice display ASD-like social communication deficits and age-dependent progressive ventricular enlargements. The latter involves increased length and beating frequency of motile cilia on ependymal cells lining ventricles. Katnal2-KO hippocampal neurons surrounded by enlarged lateral ventricles show progressive synaptic deficits that correlate with ASD-like transcriptomic changes involving synaptic gene down-regulation. Importantly, early postnatal Katnal2 re-expression prevents ciliary, ventricular, and behavioral phenotypes in Katnal2-KO adults, suggesting a causal relationship and a potential treatment. Therefore, Katnal2 negatively regulates ependymal ciliary function and its deletion in mice leads to ependymal ciliary hyperfunction and hydrocephalus accompanying ASD-related behavioral, synaptic, and transcriptomic changes. Mutations in the microtubule regulatory protein Katnal2 have been linked to autism. This study finds that loss of Katnal2 in mice leads to autism-related phenotypes, which are driven in part by altered ciliary function in the lateral ventricles. [ABSTRACT FROM AUTHOR]

Indigenous and were used to study genetic diversity and population structure analyses. Polymorphism information content (PIC) values ranged from 0.0 to 0.5, with 21,285 SNP markers (35%) being in the lowest PIC value range (0 to 0.15) while 13,511 (commercial chickens have developed unique adaptations to their environments, which may include nutrition, pathogens, and thermal stress. Besides, environmental pressures and artificial selection have generated significant genome-wide divergence in chickens, as those selection pressures contribute a considerable evolutionary force to phenotypic and genotypic differentiation. Herein, we determined genomic diversity of indigenous chickens from semi-deciduous rainforest (SDR), coastal savannah (CS) and Guinea savannah (GS) agro-ecological zones (AEZs) in Ghana and commercial crossbreds (CC) reared at the Kwame Nkrumah University of Science and Technology (KNUST). We generated SNP markers from 82 chickens (62 indigenous chicken ecotypes and 26 commercial crossbred ecotype) using DArT-Seq technology. A total of 85,396 SNP markers were generated and after filtering the data, 58,353 markers 21%) were in the highest PIC value range (0.45 to 0.50). The CC were more genetically diverse than the indigenous birds, with the highest expected heterozygosity value of 0.220. Between the commercial crossbreds population and the indigenous ecotypes, pairwise FST values were estimated to be 0.105 between CS, 0.096 between SDF, and 0.133 between GS. Furthermore, PCA analysis showed that the CC, SDF and GS chickens clustered together and are genetically distant from the commercial crossbred. We herein show that chickens from the AEZs studied can be considered as one population. However, due the abundance of agro-byproducts in the SDR compared to the CS and GS, chickens from the SDR AEZ had better growth compared to their counterparts. It is suggested that the genetic diversity within the local ecotypes could form the basis for genetic improvement. [ABSTRACT FROM AUTHOR]

Discrepancies between the measurement of body mass index (BMI) and metabolic health status have been described for the onset of metabolic diseases. Studying novel biomarkers, some of which are associated with metabolic syndrome, can help us to understand the differences between metabolic health (MetH) and BMI. A group of 1469 young adults with pre-specified anthropometric and blood biochemical parameters were selected. Of these, 80 subjects were included in the downstream analysis that considered their BMI and MetH parameters for selection as follows: norm weight metabolically healthy (MHNW) or metabolically unhealthy (MUNW); overweight/obese metabolically healthy (MHOW) or metabolically unhealthy (MUOW). Our results showed for the first time the differences when the MetH status and the BMI are considered as global MetH statures. First, all the evaluated miRNAs presented a higher expression in the metabolically unhealthy group than the metabolically healthy group. The higher levels of leptin, IL-1b, IL-8, IL-17A, miR-221, miR-21, and miR-29 are directly associated with metabolic unhealthy and OW/OB phenotypes (MUOW group). In contrast, high levels of miR34 were detected only in the MUNW group. We found differences in the SIRT1-PGC1α pathway with increased levels of SIRT1+ cells and diminished mRNA levels of PGCa in the metabolically unhealthy compared to metabolically healthy subjects. Our results demonstrate that even when metabolic diseases are not apparent in young adult populations, MetH and BMI have a distinguishable phenotype print that signals the potential to develop major metabolic diseases. [ABSTRACT FROM AUTHOR]

Lymphangiogenesis is induced by local pro-lymphatic growth factors and bone marrow (BM)-derived myeloid-lymphatic endothelial cell progenitors (M-LECP). We previously showed that M-LECP play a significant role in lymphangiogenesis and lymph node metastasis in clinical breast cancer (BC) and experimental BC models. We also showed that differentiation of mouse and human M-LECP can be induced through sequential activation of colony stimulating factor-1 (CSF-1) and Toll-like receptor-4 (TLR4) pathways. This treatment activates the autocrine interleukin-10 (IL-10) pathway that, in turn, induces myeloid immunosuppressive M2 phenotype along with lymphatic-specific proteins. Because IL-10 is implicated in differentiation of numerous lineages, we sought to determine whether this pathway specifically promotes the lymphatic phenotype or multipotent progenitors that can give rise to M-LECP among other lineages. Analyses of BM cells activated either by CSF-1/TLR4 ligands in vitro or orthotopic breast tumors in vivo showed expansion of stem/progenitor population and coincident upregulation of markers for at least four lineages including M2-macrophage, lymphatic endothelial, erythroid, and T-cells. Induction of cell plasticity and multipotency was IL-10 dependent as indicated by significant reduction of stem cell markers and those for multiple lineages in differentiated cells treated with anti-IL-10 receptor (IL-10R) antibody or derived from IL-10R knockout mice. However, multipotent CD11b+/Lyve-1+/Ter-119+/CD3e+ progenitors detected in BM appeared to split into a predominant myeloid-lymphatic fraction and minor subsets expressing erythroid and T-cell markers upon establishing tumor residence. Each sub-population was detected at a distinct intratumoral site. This study provides direct evidence for differences in maturation status between the BM progenitors and those reaching tumor destination. The study results suggest preferential tumor bias towards expansion of myeloid-lymphatic cells while underscoring the role of IL-10 in early BM production of multipotent progenitors that give rise to both hematopoietic and endothelial lineages. [ABSTRACT FROM AUTHOR]