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Post-translational modification by Small Ubiquitin-like Modifier (SUMO) proteins regulates numerous cellular processes. This modification involves the covalent and reversible attachment of SUMO to target proteins through an isopeptide bond, using a cascade of E1, E2 and E3 SUMOylation enzymes. Most functions of SUMO depend on the establishment of non-covalent protein-protein interactions between SUMOylated substrates and their binding partners. The vast majority of these interactions involve a conserved surface in the SUMO protein and a SUMO interacting motif (SIM), a short stretch of hydrophobic amino acids and an acidic region, in the interactor protein. Despite single SUMO-SIM interactions are relatively weak, they can have a huge impact at different levels, altering the activity, localization and stability of proteins, triggering the formation of macromolecular assemblies or inducing phase separation. Moreover, SUMO-SIM interactions are ubiquitous in most enzymes of the SUMO pathway, and play essential roles in SUMO conjugation and deconjugation. Here, we analyze the role of SUMO-SIM contacts in SUMO enzymes and targets and discuss how this humble interaction participates in SUMOylation reactions and mediates the outcome of this essential post-translational modification.

Activating transcription factors, ATFs, are a group of bZIP transcription factors that act as homodimers or heterodimers with a range of other bZIP factors. In general, ATFs respond to extracellular signals, indicating their important roles in maintaining homeostasis. The ATF family includes ATF1, ATF2, ATF3, ATF4, ATF5, ATF6, and ATF7. Consistent with the diversity of cellular processes reported to be regulated by ATFs, the functions of ATF are also diverse. ATFs play an important role in cell proliferation, apoptosis, differentiation and inflammation-related pathological processes. The expression and phosphorylation status of ATFs are also related to neurodegenerative diseases and polycystic kidney disease. Various miRNAs target ATF to regulate cancer proliferation, apoptosis, autophagy, sensitivity and resistance to radiotherapy and chemotherapy. Moreover, ATFs are necessary to maintain cell redox homeostasis. Therefore, deepening our understanding of the regulation and function of ATFs will provide insights into the basic regulatory mechanisms that influence how cells integrate extracellular and intracellular signals into genomic responses through transcription factors. Under pathological conditions, especially in cancer biology and response to treatment, the characterization of ATF dysfunction is important for understanding how to therapeutically utilize ATF2 or other pathways controlled by transcription factors. In this review, we will demonstrate how ATF1, ATF2, ATF3, ATF4, ATF5, ATF6, and ATF7 function in promoting or suppressing cancer development and identify their roles in tumour immunotherapy.

This repository contains supplementary figures and table for Repapi et al (2022):Integration of single-cell RNA-Seq and CyTOF data characterises heterogeneity of rare cell subpopulations

In most eukaryotes, the largest subunit of RNAPII, Rpb1, contains a conserved carboxyterminal domain (CTD) containing a canonical structure of heptapeptide repeats. Two protein complexes of interest, Mediator and Integrator, are known to interact with this CTD in all eukaryotic models they have been described in to date. Recently, orthologs of Mediator and Integrator subunits have been identified within the ciliated protozoan Tetrahymena thermophila; one of the few eukaryotic lineages to lack a canonically organized CTD. To begin to characterize putative Mediator and Integrator complexes within T. thermophila, I engineered appropriate macronuclear tagging and knockout cassettes. Although the Tetrahymena MED31 ortholog was unable to rescue the slow growth phenotype of a yeast MED31 knockout, or co-purify with yeast Med8-TAP, I identified subunit Med3 as a member of the Med31 interactome in T. thermophila through tandem affinity purification coupled with mass spectrometry. I also targeted the Tetrahymena INTS6 locus for knockout as determined by colony PCR. If Mediator and Integrator exist in Tetrahymena despite its divergent CTD of Rpb1, perhaps these complexes have CTD-independent functions beyond what can be effectively studied using conventional model systems.

Motivation Recombination is one of the essential genetic processes for sexually reproducing organisms, which can happen more frequently in some regions, called recombination hotspots. Although several factors, such as PRDM9 binding motifs, are known to be related to the hotspots, their contributions to the recombination hotspots have not been quantified, and other determinants are yet to be elucidated. Here, we propose a computational method, RHSNet, based on deep learning and signal processing, to identify and quantify the hotspot determinants in a purely data-driven manner, utilizing datasets from various studies, populations, sexes and species. Results RHSNet can significantly outperform other sequence-based methods on multiple datasets across different species, sexes and studies. In addition to being able to identify hotspot regions and the well-known determinants accurately, more importantly, RHSNet can quantify the determinants that contribute significantly to the recombination hotspot formation in the relation between PRDM9 binding motif, histone modification and GC content. Further cross-sex, cross-population and cross-species studies suggest that the proposed method has the generalization power and potential to identify and quantify the evolutionary determinant motifs. Availability and implementation https://github.com/frankchen121212/RHSNet. Supplementary information Supplementary data are available at Bioinformatics online.

Gray water footprint has been widely used as an indicator to quantify the water environmental impact of textile products. Traditionally, gray water footprint values are determined by the largest gray water footprint value of the typical water pollutant. The performances of other critical compounds that coexist in wastewater are disregarded. To mitigate these shortcomings associated with gray water footprint accounting and assessment, an improved gray water footprint calculation and assessment framework is proposed in this study. The diffusion and attenuation process of pollutants in rivers was considered for the comprehensive accounting and evaluation of the impacts caused by various pollutants in discharged wastewater. Polyester fabric production was used to illustrate the application of the improved gray water footprint calculation and assessment method. The results revealed that chemical oxygen demand caused the most severe water eutrophication impact and antimony caused the most severe water ecotoxicity impact. The comprehensive evaluation of improved gray water footprint indicated that alkali peeling process caused the largest water environmental impact during polyester fabric production.

Various subunits of mammalian SWI/SNF chromatin remodeling complexes display loss-of-function mutations characteristic of tumor suppressors in different cancers, but an additional role for SWI/SNF supporting cell survival in distinct cancer contexts is emerging. In particular, genetic dependence on the catalytic subunit BRG1/SMARCA4 has been observed in acute myelogenous leukemia (AML), yet the feasibility of direct therapeutic targeting of SWI/SNF catalytic activity in leukemia remains unknown. Here, we evaluated the activity of dual BRG1/BRM ATPase inhibitors across a genetically diverse panel of cancer cell lines and observed that hematopoietic cancer cell lines were among the most sensitive compared with other lineages. This result was striking in comparison with data from pooled short hairpin RNA screens, which showed that only a subset of leukemia cell lines display sensitivity to BRG1 knockdown. We demonstrate that combined genetic knockdown of BRG1 and BRM is required to recapitulate the effects of dual inhibitors, suggesting that SWI/SNF dependency in human leukemia extends beyond a predominantly BRG1-driven mechanism. Through gene expression and chromatin accessibility studies, we show that the dual inhibitors act at genomic loci associated with oncogenic transcription factors, and observe a downregulation of leukemic pathway genes, including MYC, a well-established target of BRG1 activity in AML. Overall, small-molecule inhibition of BRG1/BRM induced common transcriptional responses across leukemia models resulting in a spectrum of cellular phenotypes. Implications: Our studies reveal the breadth of SWI/SNF dependency in leukemia and support targeting SWI/SNF catalytic function as a potential therapeutic strategy in AML.

Selection of the appropriate DNA double-strand break (DSB) repair pathway is decisive for genetic stability. It is proposed to act according to two steps: 1-canonical nonhomologous end-joining (C-NHEJ) versus resection that generates single-stranded DNA (ssDNA) stretches; 2-on ssDNA, gene conversion (GC) versus nonconservative single-strand annealing (SSA) or alternative end-joining (A-EJ). Here, we addressed the mechanisms by which RAD51 regulates this second step, preventing nonconservative repair in human cells. Silencing RAD51 or BRCA2 stimulated both SSA and A-EJ, but not C-NHEJ, validating the two-step model. Three different RAD51 dominant-negative forms (DN-RAD51s) repressed GC and stimulated SSA/A-EJ. However, a fourth DN-RAD51 repressed SSA/A-EJ, although it efficiently represses GC. In living cells, the three DN-RAD51s that stimulate SSA/A-EJ failed to load efficiently onto damaged chromatin and inhibited the binding of endogenous RAD51, while the fourth DN-RAD51, which inhibits SSA/A-EJ, efficiently loads on damaged chromatin. Therefore, the binding of RAD51 to DNA, rather than its ability to promote GC, is required for SSA/A-EJ inhibition by RAD51. We showed that RAD51 did not limit resection of endonuclease-induced DSBs, but prevented spontaneous and RAD52-induced annealing of complementary ssDNA in vitro. Therefore, RAD51 controls the selection of the DSB repair pathway, protecting genome integrity from nonconservative DSB repair through ssDNA occupancy, independently of the promotion of CG.

Background Circular RNA (circRNA), a class of RNA molecule with a loop structure, has recently attracted researchers due to its diverse biological functions and potential biomarkers of human diseases. Most of the current circRNA detection methods from RNA-sequencing (RNA-Seq) data utilize the mapping information of paired-end (PE) reads to eliminate false positives. However, much of the practical RNA-Seq data such as cross-linking immunoprecipitation sequencing (CLIP-Seq) data usually contain single-end (SE) reads. It is not clear how well these tools perform on SE RNA-Seq data. Results In this study, we present a systematic evaluation of six advanced RNA-based methods and two CLIP-Seq based methods for detecting circRNAs from SE RNA-Seq data. The performances of the methods are rigorously assessed based on precision, sensitivity, F1 score, and true discovery rate. We investigate the impacts of read length, false positive ratio, sequencing depth and PE mapping information on the performances of the methods using simulated SE RNA-Seq simulated datasets. The real datasets used in this study consist of four experimental RNA-Seq datasets with ≥100bp read length and 124 CLIP-Seq samples from 45 studies that contain mostly short-read (≤50bp) RNA-Seq data. The simulation study shows that the sensitivities of most of the methods can be improved by increasing either read length or sequencing depth, and that the levels of false positive rates significantly affect the precision of all methods. Furthermore, the PE mapping information can improve the method’s precision but can not always guarantee the increase of F1 score. Overall, no method is dominant for all SE RNA-Seq data. The RNA-based methods perform better for the long-read datasets but are worse for the short-read datasets. In contrast, the CLIP-Seq based methods outperform the RNA-Seq based methods for all the short-read samples. Combining the results of these methods can significantly improve precision in the CLIP-Seq data. Conclusions The results provide a systematic evaluation of circRNA detection methods on SE RNA-Seq data that would facilitate researchers’ strategies in circRNA analysis.

Single-cell RNA sequencing (scRNA-seq) enables molecular characterization of complex biological tissues at high resolution. The requirement of single-cell extraction, however, makes it challenging for profiling tissues such as adipose tissue, for which collection of intact single adipocytes is complicated by their fragile nature. For such tissues, single-nucleus extraction is often much more efficient and therefore single-nucleus RNA sequencing (snRNA-seq) presents an alternative to scRNA-seq. However, nuclear transcripts represent only a fraction of the transcriptome in a single cell, with snRNA-seq marked with inherent transcript enrichment and detection biases. Therefore, snRNA-seq may be inadequate for mapping important transcriptional signatures in adipose tissue. In this study, we compare the transcriptomic landscape of single nuclei isolated from preadipocytes and mature adipocytes across human white and brown adipocyte lineages, with whole-cell transcriptome. We show that snRNA-seq is capable of identifying the broad cell types present in scRNA-seq at all states of adipogenesis. However, we also explore how and why the nuclear transcriptome is biased and limited, as well as how it can be advantageous. We robustly characterize the enrichment of nuclear-localized transcripts and adipogenic regulatory lncRNAs in snRNA-seq, while also providing a detailed understanding for the preferential detection of long genes upon using this technique. To remove such technical detection biases, we propose a normalization strategy for a more accurate comparison of nuclear and cellular data. Finally, we show successful integration of scRNA-seq and snRNA-seq data sets with existing bioinformatic tools. Overall, our results illustrate the applicability of snRNA-seq for the characterization of cellular diversity in the adipose tissue.

RNA sequencing (RNA-seq) has revolutionized basic biomedical research by studying the transcriptome at high resolution, and thus it has been proved to be very successful for understanding the molecular mechanisms of cancers. For example, RNA-seq has facilitated a comprehensive and multidimensional mapping of the key genomic changes that lead to various types of cancers. Nevertheless, the heterogeneous nature of cancer tissues has always been a problem. To overcome this challenge, single-cell RNA sequencing (scRNA-seq) has emerged as the most powerful tool to characterize cancer tissues by enhancing our knowledge of transcriptome at a single-cell resolution. In addition to disentangling the heterogeneity problem, scRNA-seq has other applications such as determining the molecular mechanisms of cellular differentiation, characterizing gene expression levels, and determining rare cell types found within cancer tissue. scRNA-Seq is used, as an emerging diagnostic tool, in tertiary healthcare settings with diverse clinical applications. Thus, the utility of scRNA-Seq in a healthcare system not only provides compelling evidence about understanding cancer biology but also points towards the development of therapeutic options in the future. The purpose of this review is to educate readers about the applications of scRNA-seq in cancer research in a wider context..

Nano drug delivery systems are a research hotspot in the field of tumor therapy. In this work, molybdenum disulfide (MoS

In Escherichia coli, the replication initiator DnaA oscillates between an ATP- and an ADP-bound state in a cell cycle-dependent manner, supporting regulation for chromosome replication. ATP–DnaA cooperatively assembles on the replication origin using clusters of low-affinity DnaA-binding sites. After initiation, DnaA-bound ATP is hydrolyzed, producing initiation-inactive ADP–DnaA. For the next round of initiation, ADP–DnaA binds to the chromosomal locus DARS2, which promotes the release of ADP, yielding the apo-DnaA to regain the initiation activity through ATP binding. This DnaA reactivation by DARS2 depends on site-specific binding of IHF (integration host factor) and Fis proteins and IHF binding to DARS2 occurs specifically during pre-initiation. Here, we reveal that Fis binds to an essential region in DARS2 specifically during pre-initiation. Further analyses demonstrate that ATP–DnaA, but not ADP–DnaA, oligomerizes on a cluster of low-affinity DnaA-binding sites overlapping the Fis-binding region, which competitively inhibits Fis binding and hence the DARS2 activity. DiaA (DnaA initiator-associating protein) stimulating ATP–DnaA assembly enhances the dissociation of Fis. These observations lead to a negative feedback model where the activity of DARS2 is repressed around the time of initiation by the elevated ATP–DnaA level and is stimulated following initiation when the ATP–DnaA level is reduced.

A rapid and confident tool to identify and diagnose bacterial pathogens with more accuracy using DNA as fingerprints is necessary. Herein, we report a smart chemosensor having a terminal adenine sticking to the thymine of single-stranded DNA (ssDNA) through supramolecular interactions and, which leaves ssDNA when the same ssDNA matches with the targeting desired DNA. We have synthesized a naked-eye coloured chemosensor with carbazole. As a model genetic material, DNA of Clavibacter michiganensis subsp. michiganensis was hybridized to ssDNA and immobilized over nitrocellulose membrane. The prepared adenine-chemosensor, by passing through the nitrocellulose-ssDNA membrane caused the formation of ssDNA nitrocellulose-ssDNA-adenine-chemosensor. FTIR results of the immobilized ssDNAs showed that the matching of same ssDNA releases the adenine-chemosensor from the surface of nitrocellulose-ssDNA that results in formation of the double stranded DNA. The selectivity of chemosensor was also confirmed with different bacterial DNA (Bacillus subtilis) as control. These data highlights accurate and reliable results of a new diagnostic kit prototype promising for further studies, which is able to diagnose DNA quickly and precisely.

NMDAR (N-methyl-d-aspartate receptor) consisted of GluN1 and GluN2, and/or GluN3 subunits. As the obligatory subunit of NMDAR, GluN1 contains variant N-terminal domain (NTD) and C-terminal domain (CTD). The CTD contains allosteric signal and mediates the metabotropic function of NMDAR, which has been confirmed by previous studies. However, the allosteric signaling mechanism of GluN1 CTD has not been studied. In our study, we found that GluN1 CTD could bind to the lipid bilayers and affect the antigen epitope of GluN1 C-terminal antibody, suggesting that membrane binding may determine the allosteric signal of GluN1 CTD. In addition, we discovered that the membrane binding of GluN1 CTD could be regulated by the phosphorylation of GluN1 CTD C1 region.

Although there are immune checkpoint inhibitors (ICIs) available for the treatment of renal cell carcinoma (RCC), the utility of PD-L1 detection by immunohistochemistry (IHC) as a predictive biomarker in clear cell RCC (ccRCC) remains controversial. Nevertheless, alternative methods for PD-L1 detection, such as RNA sequencing (RNA-Seq), may be clinically useful in ccRCC; therefore, we sought to determine the ability of RNA-Seq to accurately and sensitively detect PD-L1 expression across different ccRCC clinical samples in comparison with IHC.Patients with ccRCC (n=127) who received treatment from Washington University in St. Louis between 2018 and 2020 were identified. Tumors from these patients were analyzed using RNA-Seq and IHC.PD-L1 detection by RNA-Seq strongly correlated with IHC (P.001), which was further validated using two independent datasets. Furthermore, RNA-Seq analysis identified an immune-enriched (higher PD-L1 positivity) and an immune-desert (lower PD-L1 positivity) microenvironment of ccRCC, which also correlated with IHC (P.00001).The results demonstrate the ability of RNA-Seq to detect PD-L1 in various ccRCC clinical samples compared to IHC. Ultimately, these findings suggest that PD-L1 detection by RNA-Seq can be further developed to determine the clinical utility of this methodology in ccRCC.

The switch/sucrose non-fermentable (SWI/SNF) complex has a crucial role in chromatin remodelling1 and is altered in over 20% of cancers2,3. Here we developed a proteolysis-targeting chimera (PROTAC) degrader of the SWI/SNF ATPase subunits, SMARCA2 and SMARCA4, called AU-15330. Androgen receptor (AR)+ forkhead box A1 (FOXA1)+ prostate cancer cells are exquisitely sensitive to dual SMARCA2 and SMARCA4 degradation relative to normal and other cancer cell lines. SWI/SNF ATPase degradation rapidly compacts cis-regulatory elements bound by transcription factors that drive prostate cancer cell proliferation, namely AR, FOXA1, ERG and MYC, which dislodges them from chromatin, disables their core enhancer circuitry, and abolishes the downstream oncogenic gene programs. SWI/SNF ATPase degradation also disrupts super-enhancer and promoter looping interactions that wire supra-physiologic expression of the AR, FOXA1 and MYC oncogenes themselves. AU-15330 induces potent inhibition of tumour growth in xenograft models of prostate cancer and synergizes with the AR antagonist enzalutamide, even inducing disease remission in castration-resistant prostate cancer (CRPC) models without toxicity. Thus, impeding SWI/SNF-mediated enhancer accessibility represents a promising therapeutic approach for enhancer-addicted cancers., PROTAC degrader–induced SWI/SNF inactivation abolishes DNA accessibility at enhancer elements of oncogenes and also tempers supra-physiologic expression of driver transcription factors, resulting in potent inhibition of tumour growth in mouse models.

During meiosis, DNA double-strand breaks (DSBs) are formed at high frequency at special chromosomal sites, called DSB hotspots, to generate crossovers that aid proper chromosome segregation. Multiple chromosomal features affect hotspot formation. In the fission yeast S. pombe the linear element proteins Rec25, Rec27 and Mug20 are hotspot determinants – they bind hotspots with high specificity and are necessary for nearly all DSBs at hotspots. To assess whether they are also sufficient for hotspot determination, we localized each linear element protein to a novel chromosomal site (ade6 with lacO substitutions) by fusion to the Escherichia coli LacI repressor. The Mug20-LacI plus lacO combination, but not the two separate lac elements, produced a strong ade6 DSB hotspot, comparable to strong endogenous DSB hotspots. This hotspot had unexpectedly low ade6 recombinant frequency and negligible DSB hotspot competition, although like endogenous hotspots it manifested DSB interference. We infer that linear element proteins must be properly placed by endogenous functions to impose hotspot competition and proper partner choice for DSB repair. Our results support and expand our previously proposed DSB hotspot-clustering model for local control of meiotic recombination.

The term ‘super enhancers’ (SE) has been widely used to describe stretches of closely localized enhancers that are occupied collectively by large numbers of transcription factors (TFs) and co-factors, and control the transcription of highly-expressed genes. Through integrated analysis of >600 DNase-seq, ChIP-seq, GRO-seq, STARR-seq, RNA-seq, Hi-C and ChIA-PET data in five human cancer cell lines, we identified a new class of autonomous SEs (aSEs) that are excluded from classic SE calls by the widely used Rank Ordering of Super-Enhancers (ROSE) method. TF footprint analysis revealed that compared to classic SEs and regular enhancers, aSEs are tightly bound by a dense array of master lineage TFs, which serve as anchors to recruit additional TFs and co-factors in trans. In addition, aSEs are preferentially enriched for Cohesins, which likely involve in stabilizing long-distance interactions between aSEs and their distal target genes. Finally, we showed that aSEs can be reliably predicted using a single DNase-seq data or combined with Mediator and/or P300 ChIP-seq. Overall, our study demonstrates that aSEs represent a unique class of functionally important enhancer elements that distally regulate the transcription of highly expressed genes.

Organ development is dictated by the regulation of genes preferentially expressed in tissues or cell types. Gene expression profiling and identification of specific genes in organs can provide insights into organogenesis. Therefore, genome-wide analysis is a powerful tool for clarifying the mechanisms of development during organogenesis as well as tooth development. Single-cell RNA sequencing (scRNA-seq) is a suitable tool for unraveling the gene expression profile of dental cells. Using scRNA-seq, we can obtain a large pool of information on gene expression; however, identification of functional genes, which are key molecules for tooth development, via this approach remains challenging. In the present study, we performed cap analysis of gene expression sequence (CAGE-seq) using mouse tooth germ to identify the genes preferentially expressed in teeth. The CAGE-seq counts short reads at the 5′-end of transcripts; therefore, this method can quantify the amount of transcripts without bias related to the transcript length. We hypothesized that this CAGE data set would be of great help for further understanding a gene expression profile through scRNA-seq. We aimed to identify the important genes involved in tooth development via bioinformatics analyses, using a combination of scRNA-seq and CAGE-seq. We obtained the scRNA-seq data set of 12,212 cells from postnatal day 1 mouse molars and the CAGE-seq data set from postnatal day 1 molars. scRNA-seq analysis revealed the spatiotemporal expression of cell type–specific genes, and CAGE-seq helped determine whether these genes are preferentially expressed in tooth or ubiquitously. Furthermore, we identified candidate genes as novel tooth-enriched and dental cell type–specific markers. Our results show that the integration of scRNA-seq and CAGE-seq highlights the genes important for tooth development among numerous gene expression profiles. These findings should contribute to resolving the mechanism of tooth development and establishing the basis for tooth regeneration in the future.

Streptomyces coelicolor A3(2) is used worldwide for genetic studies, and its complete genome sequence was published in 2002. However, as the whole genome of the type strain of S. coelicolor has not been analyzed, the relationship between S. coelicolor A3(2) and the type strain is not yet well known. To clarify differences in their biosynthetic potential, as well as their taxonomic positions, we sequenced whole genomes of S. coelicolor NBRC 12854T and type strains of its closely related species—such as Streptomyces daghestanicus, Streptomyces hydrogenans, and Streptomyces violascens—via PacBio. Biosynthetic gene clusters for polyketides and non-ribosomal peptides were surveyed by antiSMASH, followed by bioinformatic analyses. Type strains of Streptomyces albidoflavus, S. coelicolor, S. daghestanicus, S. hydrogenans, and S. violascens shared the same 16S rDNA sequence, but S. coelicolor A3(2) did not. S. coelicolor A3(2) and S. coelicolor NBRC 12854T can be classified as Streptomycesanthocyanicus and S. albidoflavus, respectively. In contrast, S. daghestanicus, S. hydrogenans, and S. violascens are independent species, despite their identical 16S rDNA sequences. S. coelicolor A3(2), S. coelicolor NBRC 12854T, S. daghestanicus NBRC 12762T, S. hydrogenans NBRC 13475T, and S. violascens NBRC 12920T each harbor specific polyketide synthase (PKS) and non-ribosomal peptide synthetase (NRPS) gene clusters in their genomes, whereas PKS and NRPS gene clusters are well conserved between S. coelicolor A3(2) and S. anthocyanicus JCM 5058T, and between S. coelicolor NBRC 12854T and S. albidoflavus DSM 40455T, belonging to the same species. These results support our hypothesis that the repertoires of PKS and NRPS gene clusters are different between different species.

Huge epidemiological and clinical studies have confirmed that black tea is a rich source of health-promoting ingredients, such as catechins and theaflavins (TFs). Furthermore, TF derivatives mainly include theaflavin (TF1), theaflavin-3-gallate (TF2A), theaflavin-3′-gallate (TF2B), and theaflavin-3,3′-digallate (TF3). All of these TFs exhibit extensive usages in pharmaceutics, foods, and traditional medication systems. Various indepth studies reported that how TFs modulates health effects in cellular and molecular mechanisms. The available literature regarding the pharmacological activities of TFs has revealed that TF3 has remarkable anti-inflammatory, antioxidant, anticancer, antiobesity, antiosteoporotic, and antimicrobial properties, thus posing significant effects on human health. The current manuscript summarizes both the chemistry and various pharmacological effects of TFs on human health, lifestyle or aging associated diseases, and populations of gut microbiota. Furthermore, the biological potential of TFs has also been focused to provide a deeper understanding of its mechanism of action.

The RNA recognition motif (RRM) binds to nucleic acids as well as proteins. More than one such domain is found in the pre-mRNA processing hnRNP proteins. While the mode of RNA recognition by RRMs is known, the molecular basis of their protein interaction remains obscure. Here we describe the mode of interaction between hnRNP L and LL with the methyltransferase SETD2. We demonstrate that for the interaction to occur, a leucine pair within a highly conserved stretch of SETD2 insert their side chains in hydrophobic pockets formed by hnRNP L RRM2. Notably, the structure also highlights that RRM2 can form a ternary complex with SETD2 and RNA. Remarkably, mutating the leucine pair in SETD2 also results in its reduced interaction with other hnRNPs. Importantly, the similarity that the mode of SETD2-hnRNP L interaction shares with other related protein-protein interactions reveals a conserved design by which splicing regulators interact with one another., Interaction between SETD2 and hnRNP L has previously been shown to be implicated in coupling gene transcription and mRNA processing. Here the authors elucidate the molecular basis of this functional interaction, showing that the RRM domain of hnRNP L possesses non-overlapping binding interfaces for engaging RNA and SETD2.

Our purpose was to investigate the effect of automated knowledge-based planning (KBP) on real-world clinical workflow efficiency, assess whether manual refinement of KBP plans improves plan quality across multiple disease sites, and develop a data-driven method to periodically improve KBP automated planning routines.Using clinical knowledge-based automated planning routines for prostate, prostatic fossa, head and neck, and hypofractionated lung disease sites in a commercial KBP solution, workflow efficiency was compared in terms of planning time in a pre-KBP (n = 145 plans) and post-KBP (n = 503) patient cohort. Post-KBP, planning was initialized with KBP (KBP-only) and subsequently manually refined (KBP +human). Differences in planning time were tested for significance using a 2-tailed Mann-Whitney U test (P.05, null hypothesis: planning time unchanged). Post-refinement plan quality was assessed using site-specific dosimetric parameters of the original KBP-only plan versus KBP +human; 2-tailed paired t test quantified statistical significance (Bonferroni-corrected P.05, null hypothesis: no dosimetric difference after refinement). If KBP +human significantly improved plans across the cohort, optimization objectives were changed to create an updated KBP routine (KBP'). Patients were replanned with KBP' and plan quality was compared with KBP +human as described previously.KBP significantly reduced planning time in all disease sites: prostate (median: 7.6 hrs → 2.1 hrs; P.001), prostatic fossa (11.1 hrs → 3.7 hrs; P = .001), lung (9.9 hrs → 2.0 hrs; P.001), and head and neck (12.9 hrs → 3.5 hrs; P.001). In prostate, prostatic fossa, and lung disease sites, organ-at-risk dose changes in KBP +human versus KBP-only were minimal (1% prescription dose). In head and neck, KBP +human did achieve clinically relevant dose reductions in some parameters. The head and neck routine was updated (KBP'KBP increased clinical efficiency by significantly reducing planning time. On average, human refinement offered minimal dose improvements over KBP-only plans. In the single disease site where KBP +human was superior to KBP-only, differences were eliminated by adjusting optimization parameters in a revised KBP routine.

Replication stress causes replication fork stalling, resulting in an accumulation of single-stranded DNA (ssDNA). Replication protein A (RPA) and CTC1-STN1-TEN1 (CST) complex bind ssDNA and are found at stalled forks, where they regulate RAD51 recruitment and foci formation in vivo. Here, we investigate crosstalk between RPA, CST, and RAD51. We show that CST and RPA localize in close proximity in cells. Although CST stably binds to ssDNA with a high affinity at low ionic strength, the interaction becomes more dynamic and enables facilitated dissociation at high ionic strength. CST can coexist with RPA on the same ssDNA and target RAD51 to RPA-coated ssDNA. Notably, whereas RPA-coated ssDNA inhibits RAD51 activity, RAD51 can assemble a functional filament and exhibit strand-exchange activity on CST-coated ssDNA at high ionic strength. Our findings provide mechanistic insights into how CST targets and tethers RAD51 to RPA-coated ssDNA in response to replication stress., During replication stress, the RPA protein complex coats single-stranded DNA to preclude RAD51 loading. Here, the authors show how RPA and CST crosstalk to regulate RAD51 activity.

Charting an organs’ biological atlas requires us to spatially resolve the entire single-cell transcriptome, and to relate such cellular features to the anatomical scale. Single-cell and single-nucleus RNA-seq (sc/snRNA-seq) can profile cells comprehensively, but lose spatial information. Spatial transcriptomics allows for spatial measurements, but at lower resolution and with limited sensitivity. Targeted in situ technologies solve both issues, but are limited in gene throughput. To overcome these limitations we present Tangram, a method that aligns sc/snRNA-seq data to various forms of spatial data collected from the same region, including MERFISH, STARmap, smFISH, Spatial Transcriptomics (Visium) and histological images. Tangram can map any type of sc/snRNA-seq data, including multimodal data such as those from SHARE-seq, which we used to reveal spatial patterns of chromatin accessibility. We demonstrate Tangram on healthy mouse brain tissue, by reconstructing a genome-wide anatomically integrated spatial map at single-cell resolution of the visual and somatomotor areas.

Purpose Single-cell RNA Sequencing (scRNA-seq) is a novel method enabling genetic characterization of tumor tissue at a single-cell level. Methods This study systematically reviewed the literature on studies using scRNA-seq to characterize head and neck squamous cell carcinomas (HNSCC). Results Seven studies were included, of which two studies performed scRNA-seq on 20 patients in total, and five studies used scRNA-seq data in a subsequent clinical study. The former mentioned two studies found intra-tumoral genetic heterogeneity among malignant cells but genetic uniformity among non-malignant cells. The five latter studies used scRNA-seq data in various ways. Three studies identified biomarkers related to predicting whether a patient would benefit from immunotherapeutic treatment. One study characterized genes related to the perineural invasion. One study identified genes to be used in diagnostics. Conclusion Further studies performing scRNA-seq on HNSCC are required to continue the ongoing development and use of scRNA-seq.

U1 small nuclear ribonucleoproteins (U1 snRNP) associates with 5' splice sites in the form of ribonucleoprotein particles, is highly conserved among species. The physiological functions of U1 snRNP in a lepidopteran model insect Bombyx mori is mostly unknown. Here we showed that U1 snRNP plays an important role in the development of silkworm. Knockout of U1 snRNP in silkworm showed either delayed or stationary 1st-instar larva development compared with the wild type group. U1 snRNP deletion mutants exhibited abnormal cellular phenotypes with enlarged cell nucleus, scanty cytoplasm, and enlarged nuclei. RNA-seq analysis revealed that genes involved in metabolic pathway, biosynthesis of secondary metabolites and steroid hormone biosynthesis were significantly affected by U1 snRNP depletion. Taken together, our study suggests that U1 snRNP homeostasis plays an important role in silkworm development. This article is protected by copyright. All rights reserved.

Supplemental Digital Content is available in the text., Patients with advanced melanoma treated with immune checkpoint inhibitors can experience ongoing disease control after treatment discontinuation without subsequent systemic anticancer therapy. We previously defined a novel outcome, treatment-free survival (TFS), as the time between protocol therapy cessation and subsequent therapy initiation/death. We assessed the effect of established prognostic variables [lactate dehydrogenase (LDH), programmed death ligand 1 status, BRAF mutation status, performance status, and sex] on TFS in different treatment scenarios: treatment until toxicity/progression with frequent early cessation (nivolumab plus ipilimumab), treatment until toxicity/progression with a well-tolerated regimen (nivolumab), and treatment for a short fixed duration (ipilimumab). Data were pooled from 1077 patients with advanced melanoma treated in the CheckMate 069 and 067 trials. TFS was defined as the area between the Kaplan–Meier curves for time to therapy cessation and time to subsequent therapy initiation/death. TFS was estimated by restricted mean (r-mean) survival time at 36 months since randomization. Clinically meaningful TFS (r-mean TFS 3.7–12.7 months) was observed across all patient subgroups. TFS was longest in patients treated with nivolumab plus ipilimumab. The largest differences in r-mean TFS were observed with LDH in the nivolumab plus ipilimumab and ipilimumab treatment groups (TFS difference 4.7 and 4.9 months, respectively). In the nivolumab group, there was little difference in TFS across subgroups (r-mean TFS 3.7–5.5 months). TFS was sensitive to prognostic subgroup differences; however, duration of treatment affected the sensitivity of TFS. These results provide further support for TFS as a clinical outcome measure.

BRCA2-mutant cells are defective in homologous recombination, making them vulnerable to the inactivation of other pathways for the repair of DNA double-strand breaks (DSBs). This concept can be clinically exploited but is currently limited due to insufficient knowledge about how DSBs are repaired in the absence of BRCA2. We show that DNA polymerase θ (POLθ)-mediated end joining (TMEJ) repairs DSBs arising during the S phase in BRCA2-deficient cells only after the onset of the ensuing mitosis. This process is regulated by RAD52, whose loss causes the premature usage of TMEJ and the formation of chromosomal fusions. Purified RAD52 and BRCA2 proteins both block the DNA polymerase function of POLθ, suggesting a mechanism explaining their synthetic lethal relationships. We propose that the delay of TMEJ until mitosis ensures the conversion of originally one-ended DSBs into two-ended DSBs. Mitotic chromatin condensation might further serve to juxtapose correct break ends and limit chromosomal fusions.

Background Alterations in genes encoding chromatin regulatory proteins are prevalent in cancers and may confer oncogenic properties and molecular changes linked to therapy resistance. However, the impact of copy number alterations (CNAs) of the SWItch/Sucrose NonFermentable (SWI/SNF) complex on the oncogenic and immunologic properties has not been systematically explored across human cancer types. Methods We comprehensively analyzed the genomic, transcriptomic and clinical data of The Cancer Genome Atlas (TCGA) dataset across 33 solid cancers. Results CNAs of the SWI/SNF components were identified in more than 25% of all queried cancers, and tumors harboring SWI/SNF CNAs demonstrated a worse overall survival (OS) than others in several cancer types. Mechanistically, the SCNA events in the SWI/SNF complex are correlated with dysregulated genomic features and oncogenic pathways, including the cell cycle, DNA damage and repair. Notably, the SWI/SNF CNAs were associated with homologous recombination deficiency (HRD) and improved clinical outcomes of platinum-treated ovarian cancer. Furthermore, we observed distinct immune infiltrating patterns and immunophenotypes associated with SWI/SNF CNAs in different cancer types. Conclusion The CNA events of the SWI/SNF components are a key process linked to oncogenesis, immune infiltration and therapeutic responsiveness across human cancers.

Double-strand break (DSB) repair choice is greatly influenced by the initial processing of DNA ends. 53BP1 limits the formation of recombinogenic single-strand DNA (ssDNA) in BRCA1-deficient cells, leading to defects in homologous recombination (HR). However, the exact mechanisms by which 53BP1 inhibits DSB resection remain unclear. Previous studies have identified two potential pathways: protection against DNA2/EXO1 exonucleases presumably through the Shieldin (SHLD) complex binding to ssDNA, and localized DNA synthesis through the CTC1-STN1-TEN1 (CST) and DNA polymerase α (Polα) to counteract resection. Using a combinatorial approach of END-seq, SAR-seq, and RPA ChIP-seq, we directly assessed the extent of resection, DNA synthesis, and ssDNA, respectively, at restriction enzyme-induced DSBs. We show that, in the presence of 53BP1, Polα-dependent DNA synthesis reduces the fraction of resected DSBs and the resection lengths in G0/G1, supporting a previous model that fill-in synthesis can limit the extent of resection. However, in the absence of 53BP1, Polα activity is sustained on ssDNA yet does not substantially counter resection. In contrast, EXO1 nuclease activity is essential for hyperresection in the absence of 53BP1. Thus, Polα-mediated fill-in partially limits resection in the presence of 53BP1 but cannot counter extensive hyperresection due to the loss of 53BP1 exonuclease blockade. These data provide the first nucleotide mapping of DNA synthesis at resected DSBs and provide insight into the relationship between fill-in polymerases and resection exonucleases.

This study was conducted to evaluate the sensitivity of Magnetic Resonance (MR) Susceptibility-Weighted Imaging (SWI) and also to compare the sensitivity of Magnetic Resonance (MR) susceptibility-Weighted Imaging (SWI) and Computed Tomography (CT), such that SWI can replace the use of CT as a standard protocol in the detection and differentiation between calcification and Hemorrhage. A series of 70 patients included in this study with clinical suspicion or known history of intracranial hemorrhage/ calcifications for follow up, were scanned using both Philips Multiva 1.5T (MRI/SWI) and Philips Ingenuity 128 slice (CT) Results showed that SWI had 100% relative sensitivity, as it was able to detect both hemorrhage and calcifications in all the cases identified in CT. In addition, SWI detected hemorrhage in 2 additional cases that were nonspecific in CT. Furthermore, SWI detected signal from micro bleeds, which was missed on CT in three cases, and also detected calcification in two cases, which were not positively identified in CT. In conclusion, Susceptibility-Weighted Imaging (SWI) is highly sensitive for the detection and differentiation of hemorrhage and calcifications using Phase reconstructed images compared to conventional MRI methods and Computed Tomography.

Raw Data -RNA-seq

This data repository contains all data and code needed to rerun the RNA-seqanalyses of the paper by Downey et al. on the hypo-osmotic stress response of Cyclotella crypticaover time. All RNA-seq data are available through the National Institutes of Health Gene Expression Omnibus (GEO) under accession number GSE206725. Further details can be found in the README-file.

This article not only shows that the CUSUM multi-chart which consists of several CUSUM charts, has the asymptotic optimal performance in jointly detecting and diagnosing the unknown change in a seq...