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Human DNA sequencing protocols have revolutionized human biology, biomedical science, and clinical practice, but still have very important limitations. One limitation is that most protocols do not separate or assemble (i.e., "phase") the nucleotide content of each of the maternally and paternally derived chromosomal homologs making up the 22 autosomal pairs and the chromosomal pair making up the pseudo-autosomal region of the sex chromosomes. This has led to a dearth of studies and a consequent underappreciation of many phenomena of fundamental importance to basic and clinical genomic science. We discuss a few protocols for obtaining phase information as well as their limitations, including those that could be used in tumor phasing settings. We then describe a number of biological and clinical phenomena that require phase information. These include phenomena that require precise knowledge of the nucleotide sequence in a chromosomal segment from germline or somatic cells, such as DNA binding events, and insight into unique cis vs. trans-acting functionally impactful variant combinations-for example, variants implicated in a phenotype governed by compound heterozygosity. In addition, we also comment on the need for reliable and consensus-based diploid-context computational workflows for variant identification as well as the need for laboratory-based functional verification strategies for validating cis vs. trans effects of variant combinations. We also briefly describe available resources, example studies, as well as areas of further research, and ultimately argue that the science behind the study of human diploidy, referred to as "diplomics," which will be enabled by nucleotide-level resolution of phased genomes, is a logical next step in the analysis of human genome biology.

The lack of preparedness for detecting the highly infectious SARS-CoV-2 pathogen, the pathogen responsible for the COVID-19 disease, has caused enormous harm to public health and the economy. It took ∼60 days for the first reverse transcription quantitative polymerase chain reaction (RT-qPCR) tests for SARS-CoV-2 infection developed by the United States Centers for Disease Control (CDC) to be made publicly available. It then took >270 days to deploy 800,000 of these tests at a time when the estimated actual testing needs required over 6 million tests per day. Testing was therefore limited to individuals with symptoms or in close contact with confirmed positive cases. Testing strategies deployed on a population scale at ‘Day Zero’ i.e., at the time of the first reported case, would be of significant value. Next Generation Sequencing (NGS) has such Day Zero capabilities with the potential for broad and large-scale testing. However, it has limited detection sensitivity for low copy numbers of pathogens which may be present. Here we demonstrate that by using CRISPR-Cas9 to remove abundant sequences that do not contribute to pathogen detection, NGS detection sensitivity of COVID-19 is comparable to RT-qPCR. In addition, we show that this assay can be used for variant strain typing, co-infection detection, and individual human host response assessment, all in a single workflow using existing open-source analysis pipelines. This NGS workflow is pathogen agnostic, and therefore has the potential to transform how both large-scale pandemic response and focused clinical infectious disease testing are pursued in the future.SIGNIFICANCE STATEMENTThe lack of preparedness for detecting infectious pathogens has had a devastating effect on the global economy and society. Thus, a ‘Day Zero’ testing strategy, that can be deployed at the first reported case and expanded to population scale, is required. Next generation sequencing enables Day Zero capabilities but is inadequate for detecting low levels of pathogen due to abundant sequences of little biological interest. By applying the CRISPR-Cas system to remove these sequences in vitro, we show sensitivity of pathogen detection equivalent to RT-qPCR. The workflow is pathogen agnostic, and enables detection of strain types, co-infections and human host response with a single workflow and open-source analysis tools. These results highlight the potential to transform future large-scale pandemic response.

Many studies have highlighted the complex and diverse basis for heterosis in inbred crops. Despite the lack of a consensus model, it is vital that we turn our attention to understanding heterosis in undomesticated, heterozygous, and polyploid species, such as willow (Salix spp.). Shrub willow is a dedicated energy crop bred to be fast-growing and high yielding on marginal land without competing with food crops. A trend in willow breeding is the consistent pattern of heterosis in triploids produced from crosses between diploid and tetraploid species. Here, we test whether differentially expressed genes are associated with heterosis in triploid families derived from diploid S. purpurea, diploid S. viminalis, and tetraploid S. miyabeana parents. Three biological replicates of shoot tips from all family progeny and parents were collected after 12 weeks in the greenhouse and RNA extracted for RNA-Seq analysis. This study provides evidence that nonadditive patterns of gene expression are correlated with nonadditive phenotypic expression in interspecific triploid hybrids of willow. Expression-level dominance was most correlated with heterosis for biomass yield traits and was highly enriched for processes involved in starch and sucrose metabolism. In addition, there was a global dosage effect of parent alleles in triploid hybrids, with expression proportional to copy number variation. Importantly, differentially expressed genes between family parents were most predictive of heterosis for both field and greenhouse collected traits. Altogether, these data will be used to progress models of heterosis to complement the growing genomic resources available for the improvement of heterozygous perennial bioenergy crops.

Mammals differ more than 100-fold in maximum lifespan. Here, we conducted comparative transcriptomics on 26 species with diverse lifespans. We identified thousands of genes with expression levels negatively or positively correlated with a species' maximum lifespan (Neg- or Pos-MLS genes). Neg-MLS genes are primarily involved in energy metabolism and inflammation. Pos-MLS genes show enrichment in DNA repair, microtubule organization, and RNA transport. Expression of Neg- and Pos-MLS genes is modulated by interventions, including mTOR and PI3K inhibition. Regulatory networks analysis showed that Neg-MLS genes are under circadian regulation possibly to avoid persistent high expression, whereas Pos-MLS genes are targets of master pluripotency regulators OCT4 and NANOG and are upregulated during somatic cell reprogramming. Pos-MLS genes are highly expressed during embryogenesis but significantly downregulated after birth. This work provides targets for anti-aging interventions by defining pathways correlating with longevity across mammals and uncovering circadian and pluripotency networks as central regulators of longevity.

MEF2C has been shown to be a critical transcription factor for neurodevelopment, whose loss-of-function mutation in humans results in MEF2C haploinsufficiency syndrome (MHS), a severe form of autism spectrum disorder (ASD)/intellectual disability (ID). Here, we use patient hiPSC-derived cerebrocortical neurons and cerebral organoids to characterize MHS deficits. Unexpectedly, we found an aberrant micro-RNA-mediated gliogenesis pathway that contributes to decreased neurogenesis. We also demonstrate network-level hyperexcitability in neurons, as evidenced by excessive synaptic and extrasynaptic activity contributing to excitatory/inhibitory (E/I) imbalance. Notably, the extrasynaptic NMDA receptor antagonist, NitroSynapsin, corrects this aberrant electrical activity associated with abnormal phenotypes. During neurodevelopment, MEF2C regulates many ASD-associated gene networks suggesting that our approach may lead to personalized therapy for multiple forms of ASD.One sentence summaryAutism-like MEF2C+/- patient hiPSC models show miRNA-mediated overproduction of astrocytes and hyperactivity of neurons.

To better combat the expansion of antibiotic resistance in pathogens, new compounds, particularly those with novel mechanisms-of-action [MOA], represent a major research priority in biomedical science. However, rediscovery of known antibiotics demonstrates a need for approaches that accurately identify potential novelty with higher throughput and reduced labor. Here we describe an explainable artificial intelligence classification methodology that emphasizes prediction performance and human interpretability by using a Hierarchical Ensemble of Classifiers model optimized with a novel feature selection algorithm called Clairvoyance; collectively referred to as a CoHEC model. We evaluated our methods using whole transcriptome responses from Escherichia coli challenged with 41 known antibiotics and 9 crude extracts while depositing 122 transcriptomes unique to this study. Our CoHEC model can properly predict the primary MOA of previously unobserved compounds in both purified forms and crude extracts at an accuracy above 99%, while also correctly identifying darobactin, a newly discovered antibiotic, as having a novel MOA. In addition, we deploy our methods on a recent E. coli transcriptomics dataset from a different strain and a Mycobacterium smegmatis metabolomics timeseries dataset showcasing exceptionally high performance; improving upon the performance metrics of the original publications. We not only provide insight into the biological interpretation of our model but also that the concept of MOA is a non-discrete heuristic with diverse effects for different compounds within the same MOA, suggesting substantial antibiotic diversity awaiting discovery within existing MOA., Author summary As antimicrobial resistance is on the rise, the need for compounds with novel targets or mechanisms-of-action [MOA] are of the utmost importance from the standpoint of public health. A major bottleneck in drug discovery is the ability to rapidly screen candidate compounds for precise MOA activity as current approaches are expensive, time consuming, and are difficult to implement in high-throughput. To alleviate this bottleneck in drug discovery, we developed a human interpretable artificial intelligence classification framework that can be used to build highly accurate and flexible predictive models. In this study, we investigated antimicrobial MOA through the transcriptional responses of Escherichia coli challenged with 41 known antibiotic compounds, 9 crude extracts, and a recently discovered (circa 2019) compound, darobactin, with novel MOA activity. We implemented a highly stringent Leave Compound Out Cross-Validation procedure to stress-test our predictive models by simulating the scenario of observing novel compounds. Furthermore, we developed a versatile feature selection algorithm, Clairvoyance, that we apply to our hierarchical ensemble of classifiers framework to build high performance explainable machine-learning models. Although the methods in this study were developed and stress-tested to predict the primary MOA from transcriptomic responses in E. coli, we designed these methods for general application to any classification problem and open-sourced the implementations in our Soothsayer Python package. We further demonstrate the versatility of these methods by deploying them on recent Mycobacterium smegmatis metabolomic and E. coli transcriptomics datasets to predict MOA with high accuracy.

The CoV disease 2019 (COVID-19) infectious disease outbreak is having a dramatic global effect on public health and the economy. As of October 2020, SARS-CoV-2 has been detected in over 189 countries, has infected over 40 million people, and is responsible for more than 1 million deaths., Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has infected over 40 million people worldwide, with over 1 million deaths as of October 2020 and with multiple efforts in the development and testing of antiviral drugs and vaccines under way. In order to gain insights into SARS-CoV-2 evolution and drug targets, we investigated how and to what extent the SARS-CoV-2 genome sequence differs from those of other well-characterized human and animal coronavirus genomes, as well as how polymorphic SARS-CoV-2 genomes are generally. We ultimately sought to identify features in the SARS-CoV-2 genome that may contribute to its viral replication, host pathogenicity, and vulnerabilities. Our analyses suggest the presence of unique sequence signatures in the 3′ untranslated region (3′-UTR) of betacoronavirus lineage B, which phylogenetically encompasses SARS-CoV-2 and SARS-CoV as well as multiple groups of bat and animal coronaviruses. In addition, we identified genome-wide patterns of variation across different SARS-CoV-2 strains that likely reflect the effects of selection. Finally, we provide evidence for a possible host-microRNA-mediated interaction between the 3′-UTR and human microRNA hsa-miR-1307-3p based on the results of multiple computational target prediction analyses and an assessment of similar interactions involving the influenza A H1N1 virus. This interaction also suggests a possible survival mechanism, whereby a mutation in the SARS-CoV-2 3′-UTR leads to a weakened host immune response. The potential roles of host microRNAs in SARS-CoV-2 replication and infection and the exploitation of conserved features in the 3′-UTR as therapeutic targets warrant further investigation. IMPORTANCE The coronavirus disease 2019 (COVID-19) outbreak is having a dramatic global effect on public health and the economy. As of October 2020, SARS-CoV-2 has been detected in over 189 countries, has infected over 40 million people, and is responsible for more than 1 million deaths. The genome of SARS-CoV-2 is small but complex, and its functions and interactions with human host factors are being studied extensively. The significance of our study is that, using extensive SARS-CoV-2 genome analysis techniques, we identified potential interacting human host microRNA targets that share similarity with those of influenza A virus H1N1. Our study results will allow the development of virus-host interaction models that will enhance our understanding of SARS-CoV-2 pathogenesis and motivate the exploitation of both the interacting viral and host factors as therapeutic targets.

372 Background: Multiple studies have suggested that the gut microbiome plays a modulatory role in ICI activity and that specific bacteria and/or cumulative microbial diversity may drive response in patients (pts) with mRCC (Routy et al Science 2018; Salgia et al Eur Urol 2020). Even though the tumor microenvironment has substantial bacterial proliferation (Heymann et al Cancer L. 2021), there is a paucity of data assessing the impact of intra-tumoral microbiota in response to ICI therapy. In this study, we sought to explore this association in pts with mRCC. Methods: Pts diagnosed with mRCC who had available RNA sequencing (RNA-seq) data collected in the course of routine clinical care and who were treated with ICIs were retrospectively identified.Intra-tumoral microbiome analysis was performed on formalin-fixed paraffin-embedded samples. Following quality and adapter trimming, RNA-seq reads were mapped to a human genome to filter host reads using the Burrows-Wheeler alignment (BWA) tool. Taxonomic classification was performed using Kraken2 and the absolute abundances of species were estimated using Bracken. The relative abundances among all non-human species were calculated. Statistical testing with Student’s t-test was performed to compare the relative abundance for all species seen within pts who responded to ICIs and those who did not. Results: Among the 28 pts (22:6, M:F) included in this analysis, 24 (86%) had clear cell histology and 20 (71%) were IMDC intermediate/poor risk. All of the samples were collected prior to starting treatment with ICIs and the majority of these (57%) were collected from the primary site. 11 pts (39%) received ICIs as first line treatment and 17 (61%) as second line. Clinical response was seen in 50% of pts included in the study and the most common rendered treatment was nivolumab (17 pts). In the overall cohort, Cutibacterium acne, Moraxella osloensis, and Pasteurella multocida had the highest relative abundances. Additionally, significant differences in relative abundances of specific bacteria were found between ICI responders and non-responders. Among these, Stenotrophomonas maltophilia (p = 0.037) and Corynebacterium sp. zg-917 (p = 0.035) had significantly higher relative abundances in pts who responded to ICIs. Conclusions: This is the first study evaluating the association between intra-tumoral microbiome and response to ICIs in pts with mRCC. Among bacteria associated with response, several have particular relevance – for instance, Corynebacterium spp. have been studied for decades as a possible adjunct to immunotherapeutic agents such as BCG. Efforts are ongoing to validate these findings in a larger cohort.

MicroRNAs (miRNAs) are small non-coding endogenous riboregulators that play significant roles in plant growth, development, metabolism, defense, and stress responses. Upland cotton is best known for its economic value as natural fiber and oil. It is also an important model for genome evolution, polyploidy effects, cell growth, and cell wall biosynthesis. The polyploid species, Gossypium hirsutum L. (2n = 52), evolved from two progenitors (2n = 26), one contributing an ancestral genome similar to A genomes of G. herbaceum and G. arboreum, and the other like the D genome of G. raimondii. There is much to be learned about Gossypium miRNAs and their gene targets, about the effects of polyploidy and their practical ramifications. In this study, small-RNA (sRNA) libraries from four Gossypium species and three tissue libraries (seed, seedling, and leaf) from G. hirsutum were constructed and analyzed using high-throughput sequencing with Illumina/MiSeq then computational prediction by MIREAP. Results showed 245 known miRNAs belonging to 67 miRNA families and 149 novel (non-redundant and redundant) miRNAs derived from 394 genomic loci. This unified study identified 21 and 33 conserved miRNA families across four Gossypium species and three tissue libraries, respectively. Similar to canonical miRNAs, the 5′ of novel miRNAs had the higher preference for U and A residues. In this study, 551 potential target genes were predicted in 45 conserved miRNA families, while 439 targets were associated with 113 novel miRNAs. The majority of the conserved (34%) and novel (22%) miRNA targets identified belonged to cellular processes and signaling. However, the functional diversity of novel miRNA targets is attributed to the tissue and species bias. Most of the identified targets were regulated by mRNA cleavage than by translational repression. These results provide a basis for better understanding regulatory networks in upland cotton (G. hirsutum) and its closest progenitors. Keywords: Cotton, Progenitor, Sequencing, Prediction, MIREAP, sRNA, miRNA, Family, Known, Novel, Gene regulation, Target

Chronic wounds are wounds that have failed to heal after 3 months of appropriate wound care. Previous reports have identified a diverse collection of bacteria in chronic wounds, and it has been postulated that bacterial profile may contribute to delayed healing. The purpose of this study was to perform a microbiome assessment of the Wound Healing and Etiology (WE-HEAL) Study cohort, including underlying comorbidities less commonly studied in the context of chronic wounds, such as autoimmune diseases, and investigate possible relationships of the wound microbiota with clinical healing trends. We examined chronic wound specimens from 60 patients collected through the WE-HEAL Study using 16S ribosomal RNA gene sequencing. A group of co-occurring obligate anaerobes was identified from taxonomic analysis guided by Dirichlet multinomial mixtures (DMM) modeling. The group includes members of the Gram-positive anaerobic cocci (GPAC) of the Clostridia class (i.e., Anaerococcus, Finegoldia, and Peptoniphilus) and additional strict anaerobes (i.e., Porphyromonas and Prevotella). We showed that the co-occurring group of obligate anaerobes not only co-exists with commonly identified wound species (such as Staphylococcus aureus, Staphylococcus epidermidis, Pseudomonas, Corynebacterium, and Streptococcus), but importantly, they could also predominate the wound microbiota. Furthermore, examination of clinical comorbidities of the WE-HEAL specimens showed that specific obligate and facultative anaerobes were significantly reduced in wounds presented with autoimmune disease. With respect to future healing trends, no association with the wound microbiome community or the abundance of individual wound species could be established. In conclusion, we identified a co-occurring obligate anaerobic community type that predominated some human chronic wounds and underrepresentation of anaerobes in wounds associated with autoimmune diseases. Possible elucidation of host environments or key factors that influence anaerobe colonization warrants further investigation in a larger cohort.

Objectives To investigate the genomic context of a novel resistance island (RI) in multiply antibiotic-resistant Acinetobacter baumannii clinical isolates and global isolates. Methods Using a combination of long and short reads generated from the Oxford Nanopore and Illumina platforms, contiguous chromosomes and plasmid sequences were determined. BLAST-based analysis was used to identify the RI insertion target. Results Genomes of four multiply antibiotic-resistant A. baumannii clinical strains, from a US hospital system, belonging to prevalent MLST ST2 (Pasteur scheme) and ST281 (Oxford scheme) clade F isolates were sequenced to completion. A class 1 integron carrying aadB (tobramycin resistance) and aadA2 (streptomycin/spectinomycin resistance) was identified. The class 1 integron was 6.8 kb, bounded by IS26 at both ends, and embedded in a new target location between an α/β-hydrolase and a reductase. Due to its novel insertion site and unique RI composition, we suggest naming this novel RI AbGRI4. Molecular analysis of global A. baumannii isolates identified multiple AbGRI4 RI variants in non-ST2 clonal lineages, including variations in the resistance gene cassettes, integron backbone and insertion breakpoints at the hydrolase gene. Conclusions A novel RI insertion target harbouring a class 1 integron was identified in a subgroup of ST2/ST281 clinical isolates. Variants of the RI suggested evolution and horizontal transfer of the RI across clonal lineages. Long- and short-read hybrid assembly technology completely resolved the genomic context of IS-bounded RIs, which was not possible using short reads alone.

Antimicrobial resistance (AMR) is an ever-growing public health problem worldwide. The low rate of antibiotic discovery coupled with the rapid spread of drug-resistant bacterial pathogens is causing a global health crisis. To facilitate the drug discovery processes, we present a large-scale study of reference antibiotic challenge bacterial transcriptome profiles, which included 37 antibiotics across 6 mechanisms of actions (MOAs) and provide an economical approach to aid in antimicrobial dereplication in the discovery process., Antimicrobial resistance (AMR) is an ever-growing public health problem worldwide. The low rate of antibiotic discovery coupled with the rapid spread of drug-resistant bacterial pathogens is causing a global health crisis. To facilitate the drug discovery processes, we present a large-scale study of reference antibiotic challenge bacterial transcriptome profiles, which included 37 antibiotics across 6 mechanisms of actions (MOAs) and provide an economical approach to aid in antimicrobial dereplication in the discovery process. We demonstrate that classical MOAs can be sorted based upon the magnitude of gene expression profiles despite some overlap in the secondary effects of antibiotic exposures across MOAs. Additionally, using gene subsets, we were able to subdivide broad MOA classes into subMOAs. Furthermore, we provide a biomarker gene set that can be used to classify most antimicrobial challenges according to their canonical MOA. We also demonstrate the ability of this rapid MOA diagnostic tool to predict and classify the expression profiles of pure compounds and crude extracts to their expression profile-associated MOA class.

In clinical practice, point-of-care diagnostic testing has progressed rapidly in the last decade. For the field of wound care, there is a compelling need to develop rapid alternatives for bacterial identification in the clinical setting, where it generally takes over 24 hours to receive a positive identification. Even new molecular and biochemical identification methods require an initial incubation period of several hours to obtain a sufficient number of cells prior to performing the analysis. Here we report the use of an inexpensive, disposable electrochemical sensor to detect pyocyanin, a unique, redox-active quorum sensing molecule released by Pseudomonas aeruginosa, in wound fluid from patients with chronic wounds enrolled in the WE-HEAL Study. By measuring the metabolite excreted by the cells, this electrochemical detection strategy eliminates sample preparation, takes less than a minute to complete, and requires only 7.5 μL of sample to complete the analysis. The electrochemical results were compared against 16S rRNA profiling using 454 pyrosequencing. Blind identification yielded 9 correct matches, 2 false negatives, and 3 false positives giving a sensitivity of 71% and specificity of 57% for detection of Pseudomonas. Ongoing enhancement and development of this approach with a view to develop a rapid point-of-care diagnostic tool is planned.

Humans are a diploid species that inherit one set of chromosomes paternally and one homologous set of chromosomes maternally. Unfortunately, most human sequencing initiatives ignore this fact in that they do not directly delineate the nucleotide content of the maternal and paternal copies of the 23 chromosomes individuals possess (i.e., they do not ‘phase’ the genome) often because of the costs and complexities of doing so. We compared 11 different widely-used approaches to phasing human genomes using the publicly available ‘Genome-In-A-Bottle’ (GIAB) phased version of the NA12878 genome as a gold standard. The phasing strategies we compared included laboratory-based assays that prepare DNA in unique ways to facilitate phasing as well as purely computational approaches that seek to reconstruct phase information from general sequencing reads and constructs or population-level haplotype frequency information obtained through a reference panel of haplotypes. To assess the performance of the 11 approaches, we used metrics that included, among others, switch error rates, haplotype block lengths, the proportion of fully phase-resolved genes, phasing accuracy and yield between pairs of SNVs. Our comparisons suggest that a hybrid or combined approach that leverages: 1. population-based phasing using the SHAPEIT software suite, 2. either genome-wide sequencing read data or parental genotypes, and 3. a large reference panel of variant and haplotype frequencies, provides a fast and efficient way to produce highly accurate phase-resolved individual human genomes. We found that for population-based approaches, phasing performance is enhanced with the addition of genome-wide read data; e.g., whole genome shotgun and/or RNA sequencing reads. Further, we found that the inclusion of parental genotype data within a population-based phasing strategy can provide as much as a ten-fold reduction in phasing errors. We also considered a majority voting scheme for the construction of a consensus haplotype combining multiple predictions for enhanced performance and site coverage. Finally, we also identified DNA sequence signatures associated with the genomic regions harboring phasing switch errors, which included regions of low polymorphism or SNV density., Author summary Humans are a diploid species that inherit one set of chromosomes paternally and one set of chromosomes maternally. Separating the nucleotide content of the maternally and paternally-derived chromosomes for an individual, i.e., ‘phasing’ that individual’s genome, is not trivial with today’s sequencing technologies. This is in part due to the fact that most available sequencing technologies generate short sequencing reads that make it hard to assemble individual homologous chromosome pairs. Phase information can be crucial for putting into context the likely functional consequences of DNA sequence variants as well as certain evolutionary and population genetics phenomena. In order to assess the reliability of current sequencing-based phasing strategies, we compared 11 different approaches using a public domain reference genome as a test case. These phasing strategies included laboratory-based experimental techniques as well as purely computational approaches. Importantly, our comparisons show that a hybrid or combined approach that leverages population-based phasing via the SHAPEIT software suite works well and can be improved with the addition of genome-wide sequence read or parental genotype data.

In light of the ongoing antimicrobial resistance crisis, there is a need to understand the role of co-pathogens, commensals, and the local microbiome in modulating virulence and antibiotic resistance. To identify possible interactions that influence the expression of virulence or survival mechanisms in both the multidrug-resistant organisms (MDROs) and human host cells, unique cohorts of clinical isolates were selected for whole genome sequencing with enhanced assembly and full annotation, pairwise co-culturing, and transcriptome profiling. The MDROs were co-cultured in pairwise combinations either with: (1) another MDRO, (2) skin commensals (Staphylococcus epidermidis and Corynebacterium jeikeium), (3) the common probiotic Lactobacillus reuteri, and (4) human fibroblasts. RNA-Seq analysis showed distinct regulation of virulence and antimicrobial resistance gene responses across different combinations of MDROs, commensals, and human cells. Co-culture assays demonstrated that microbial interactions can modulate gene responses of both the target and pathogen/commensal species, and that the responses are specific to the identity of the pathogen/commensal species. In summary, bacteria have mechanisms to distinguish between friends, foe and host cells. These results provide foundational data and insight into the possibility of manipulating the local microbiome when treating complicated polymicrobial wound, intra-abdominal, or respiratory infections.

BACKGROUND In vitro generation of red blood cells (RBCs) from hematopoietic stem cells (HSCs) has been reported, but the collection of 1 × 105 to 1 × 106 CD34+ cells present in cord and peripheral blood is too small for expansion to 1 × 1012 cells in 1 unit of RBCs. We transduced JAK2V617F gene, the most common mutation with polycythemia vera (PV), into cord blood–derived CD34+ cells. This PV model was expected to increase cell proliferation without the addition of erythropoietin (EPO) in early phase of differentiation. STUDY DESIGN AND METHODS Empty vector (control), wild-type JAK2 (wJAK2), and mutant JAK2V617F (mJAK2) were transduced into CD34+ cells using a lentivirus system. The CD34+ cells were then differentiated to the RBCs in a culture system. The cells were analyzed for cell number, differential count, and morphologic changes. Cultured RBCs were tested for oxygen equilibrium. RESULTS wJAK2- and mJAK2-transduced cells showed higher proliferation capacity until Day 21 than control cells; interestingly, only mJAK2-transduced cells were highly increased on Day 7 during EPO-free culture. However, both wJAK2- and mJAK2-tranduced cells had more delayed differentiation than control, but they had a higher portion of completely matured RBCs and orthochromatic erythroblasts. Furthermore, mJAK2-tranduced cells showed more differentiation into RBCs than wJAK2-transduced cells and they had a normal hemoglobin dissociation curve. CONCLUSION This is the first trial to use a PV erythropoiesis model for RBC differentiation from stem cells. The transduction of HSCs with mJAK2 increased their proliferation capacity in EPO-free culture conditions. This model may also be useful for investigating the pathogenesis of PV.

The heritability of gene expression is critical in understanding heterosis and is dependent on allele-specific regulation by local and remote factors in the genome. We used RNA-Seq to test whether variation in gene expression among F1 and F2 intraspecific Salix purpurea progeny is attributable to cis- and trans-regulatory divergence. We assessed the mode of inheritance based on gene expression levels and allele-specific expression for F1 and F2 intraspecific progeny in two distinct tissue types: shoot tip and stem internode. In addition, we explored sexually dimorphic patterns of inheritance and regulatory divergence among F1 progeny individuals. We show that in S. purpurea intraspecific crosses, gene expression inheritance largely exhibits a maternal dominant pattern, regardless of tissue type or pedigree. A significantly greater number of cis- and trans-regulated genes coincided with upregulation of the maternal parent allele in the progeny, irrespective of the magnitude, whereas the paternal allele was higher expressed for genes showing cis × trans or compensatory regulation. Importantly, consistent with previous genetic mapping results for sex in shrub willow, we have delimited sex-biased gene expression to a 2 Mb pericentromeric region on S. purpurea chr15 and further refined the sex determination region. Altogether, our results offer insight into the inheritance of gene expression in S. purpurea as well as evidence of sexually dimorphic expression which may have contributed to the evolution of dioecy in Salix.

Chronic inflammation is one of the main causes of cancer, yet the molecular mechanism underlying this effect is not fully understood. In this study, we identified FAT10 as a potential target gene of STAT3, the expression of which is synergistically induced by NFκB co-stimulation. STAT3 binding stabilizes NFκB on the FAT10 promoter and leads to maximum induction of FAT10 gene expression. Increased FAT10 represses the transcriptional activity of the tumor suppressor p53, a protein that accelerates the protein degradation of FAT10. This FAT10-p53 double-negative regulation is critical in the control of tumorigenesis, as overexpressed FAT10 facilitates the tumor progression in the solid tumor model. In conclusion, transcriptional synergy between STAT3 and NFκB functions to put weight on FAT10 in the mutually inhibitory FAT10-p53 regulatory loop and thus favors tumorigenesis under inflammatory conditions.

Summary: We present a web server to predict the functional effect of single or multiple amino acid substitutions, insertions and deletions using the prediction tool PROVEAN. The server provides rapid analysis of protein variants from any organisms, and also supports high-throughput analysis for human and mouse variants at both the genomic and protein levels. Availability and implementation: The web server is freely available and open to all users with no login requirements at http://provean.jcvi.org. Contact: achan@jcvi.org Supplementary information: Supplementary data are available at Bioinformatics online.

The optimization of analytical method for the thermal desorption of seven VOCs (volatile organic compounds) by TD-GC/MS (thermal desorption-gas chromatograph-mass spectrometer) with solid phase sorbent tube, and comparative analysis for the determination of VOCs plotted by standard sorbent tubes prepared using both gas phase and liquid phase materials were investigated. The result of paired t-test showed that a liquid phase standard sorbent tube method was in agreement with a gas phase standard sorbent tube method for six species of VOCs including benzene, toluene, ethylbenzene, o-, m-, and p-xylene except for styrene at the significance level (α=0.01), while the 15.6% of difference in response factor between both of gas phase and liquid phase standard plotting for the determination of styrene showed that both methods were significantly different at the significance level. Therefore, the liquid phase standard plotting method was employed to reduce erroneous data for the determination of styrene including BTEX. Under the optimized analytical method by liquid phase standard sorbent tube, recovery was between 100±5% for 7 species of VOCs, reproducibility ranged from 0.3 to 7.7%, and method detection limit (MDL) ranged from 0.01 µg/m 3 for o-xylene to 0.27 µg/m 3 for toluene. The optimized standard method was applied to determine VOCs VOCs from indoor air of of dormitory, one bedroom apartment, and a new car. 요약 : 본 연구는 고체 흡착관과 TD-GC/MS를 이용하여 7종의 휘발성 유기화합물에 대한 열탈착 분석

A simultaneous analytical method has been developed for the fluorimetric determination of haloacetonitriles (HANs) [dichloroacetonitrile (DCAN), trichloroacetonitrile (TCAN), dibromoacetonitrile (DBAN), haloacetamides [dichloroacetamide (DCAD), and trichloroacetamde (TCAD)] in drinking water by using the combined on-line perconcentration/reversed phase liquid chromatography (RPLC)-postcolumn detection system. This on-line perconcentration system was achieved by employing a precolumn packed with a commercial solid phase extraction (SPE) sorbent for the enrichment and purification of the target analytes. The haloacetonitriles and haloacetamides were separated on CN analytical column in a 7.5% methanol-0.02 M phosphate buffered mobile phase at pH 3. The column effluents were reacted with postcolumn reagents of ophthaldialdehyde (OPA) and sulfite ion at pH 11.5, to produce a highly fluorescent isoindole fluorophore, which were measured with a fluorescence detector. Under the optimized conditions for RPLC and the postcolumn derivatization system all of the coefficient of determination of the standard calibration curves for the target analytes were over 0.99 and had a linear range from 5 to 100 µg/L. The detection limits showed 1.6 µg/L for DCAD, 0.1 µg/L for TCAD, 0.6 µg/L for DCAN, 1.6 µg/L for TCAN and 1 µg/L for DBAN, and the recoveries were ranged from 64 to 99% except for DCAD with precisions less than 4.9% in distilled water, and from 72(± 4%) to 116%(± 2%) in tap water.

Department of Chemistry, Hannam University, Daejeon 305-811, KoreaReceived November 17, 2011, Accepted July 16, 2012Key Words : Flame retardants, High impact polystyrene, Extraction efficiency, Certified reference material(CRM), Solubility parameterPolybrominated diphenyl ethers (PBDEs) are commonflame retardants that are used in a wide variety of productssuch as computer casing and carpet.