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Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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bioRxiv2018

Predicting clone genotypes from tumor bulk sequencing of multiple samples

MotivationAnalyses of data generated from bulk sequencing of tumors have revealed extensive genomic heterogeneity within patients. Many computational methods have been developed to enable the inference of genotypes of tumor cell populations (clones) from bulk sequencing data. However, the relative and absolute accuracy of available computational methods in estimating clone counts and clone genotypes is not yet known.\n\nResultsWe have assessed the performance of nine methods, including eight previously-published and one new method (CloneFinder), by analyzing computer simulated datasets. CloneFinder, LICHeE, CITUP, and cloneHD inferred clone genotypes with low error (<5% per clone) for a majority of datasets in which the tumor samples contained evolutionarily-related clones. Computational methods did not perform well for datasets in which tumor samples contained mixtures of clones from different clonal lineages. Generally, the number of clones was underestimated by cloneHD and overestimated by Phy-loWGS, and BayClone2, Canopy, and Clomial required prior information regarding the number of clones. AncesTree and Canopy did not produce results for a large number of datasets.\n\nConclusionsDeconvolution of clone genotypes from single nucleotide variant (SNV) frequency differences among tumor samples remains challenging, so there is a need to develop more accurate computational methods and robust software for clone genotype inference.\n\nAvailability and ImplementationCloneFinder is implemented in Python and is available from https://github.com/gstecher/CloneFinderAPI.\n\nContacts.kumar@temple.edu\n\nSupplementary informationSupplementary data are available at Bioinformatics online

cancer biology↗

bioRxiv2018

A novel amidase signature family amidase from the marine actinomycete Salinispora arenicola CNS-205

We cloned a new gene from the amidase signature (AS) family, designated am, from the marine actinomycete Salinispora arenicola CNS-205. As indicated by bioinformatics analysis and site-directed mutagenesis, the AM protein belonged to the AS family. AM was expressed, purified, and characterised in Escherichia coli BL21 (DE3), and the AM molecular mass was determined to be 51 kDa. The optimal temperature and pH were 40 {degrees}C and pH 8.0, respectively. AM exhibited a wide substrate spectrum and showed amidase, aryl acylamidase, and acyl transferase activities. AM had high activity towards aromatic and aliphatic amides. The AM substrate specificity for anilides was very narrow; only propanil could be used as an effective substrate. The extensive substrate range of AM indicates it may have broad potential applications in biosynthetic processes and biodegradation.

molecular biology↗

bioRxiv2018

Identification and characterization of conserved and divergent genes encoding the nuclear envelope LINC complex in maize (Zea mays L.).

The LINC (Linker of Nucleoskeleton to Cytoskeleton) complex is an essential multi-protein structure spanning the nuclear envelope. It connects the cytoplasm to the nucleoplasm, functions to maintain nuclear shape and architecture, and regulates chromosome dynamics during cell division. Knowledge of LINC complex composition and function in the plant kingdom is primarily limited to Arabidopsis, but critically missing from the evolutionarily distant monocots which include grasses, the most important agronomic crops worldwide. To fill this knowledge gap, we identified and characterized 22 maize genes, including a new grass-specific KASH gene family. Using bioinformatic, biochemical, and cell biological approaches, we provide evidence that representative KASH candidates localize to the nuclear periphery and interact with ZmSUN2 in vivo. FRAP experiments using domain-deletion constructs verified that this SUN-KASH interaction was dependent on the SUN but not the coiled-coil domain of ZmSUN2. A summary working model is proposed for the entire maize LINC complex encoded by conserved and divergent gene families. These findings expand our knowledge of the plant nuclear envelope in a model grass species, with implications for both basic and applied cellular research.\n\nSUMMARY STATEMENTGenes encoding maize candidates for the core LINC and associated complex proteins have been comprehensively identified with functional validation by one or more assays for several of the KASH genes.

cell biology↗

bioRxiv2018

Long-read metagenomics reveals cryptic and abundant marine viruses

Marine viruses impact global biogeochemical cycles via their influence on host community structure and function, yet our understanding of viral ecology is constrained by limitations in culturing of important hosts and the lack of a universal gene to facilitate community surveys. Short-read viral metagenomic studies have provided clues to viral function and first estimates of global viral gene abundance and distribution. However, short-read assemblies are confounded by populations with high levels of strain evenness and nucleotide diversity (microdiversity), limiting assembly of some of the most abundant viruses on Earth. Assembly across genomic islands which likely contain niche-defining genes that drive ecological speciation is also challenging. While such populations and features are successfully captured by single-virus genomics and fosmid-based approaches, both techniques require considerable cost and technical expertise. Here we established a low-cost, low-input, high throughput alternative method for improving assembly of viral metagenomics using long read technology. Named VirION (Viral, long-read metagenomics via MinION sequencing), our sequencing approach and complementary bioinformatics pipeline (i) increased number and completeness of assembled viral genomes compared to short-read sequencing methods; (ii) captured populations of abundant viruses with high microdiversity missed by short-read methods and (iii) captured more and longer genomic islands than short-read methods. Thus, VirION provides a high throughput and cost-effective alternative to fosmid and single-virus genomic approaches to more comprehensively explore viral communities in nature.

genomics↗

bioRxiv2018

Low-dose cadmium potentiates lung inflammatory response to 2009 pandemic H1N1 influenza virus in mice

BACKGROUNDCadmium (Cd) is a toxic, pro-inflammatory metal ubiquitous in the diet that accumulates in body organs due to inefficient elimination. Many individuals exposed to dietary Cd are also infected by seasonal influenza virus. The H1N1 strain causes mild to severe pneumonia which can be fatal.\n\nOBJECTIVESTo determine the influence of low-dose Cd exposure on inflammatory responses to H1N1 influenza A virus.\n\nMETHODSWe exposed mice to low-dose (1 mg CdCl2/l) Cd or vehicle (water) for 16 weeks prior to infection with a sub-lethal dose of H1N1. Lung inflammation was assessed by histopathology and flow cytometry. We used a combination of transcriptomics, metabolomics and bioinformatics to determine the molecular associations of inflammatory cells important in Cd-exacerbated responses.\n\nRESULTSCd-treated mice had increased lung tissue inflammatory cells, including neutrophils, monocytes, T lymphocytes and dendritic cells, following H1N1 infection. Lung genetic responses to infection (increasing TNF-a, interferon and complement, and decreasing myogenesis) were also exacerbated. Global correlations with immune cell counts, leading edge gene transcripts and metabolites revealed that Cd increased correlation of myeloid immune cells with pro-inflammatory genes, particularly interferon-{gamma}, and metabolites in amino acid, nucleobase, glycerophospholipid and vitamin B3 pathways.\n\nDISCUSSIONCd burden in mice increased inflammation in response to sub-lethal H1N1 challenge, which was coordinated by genetic and metabolic responses, and could provide new targets for intervention against lethal inflammatory pathology of clinical H1N1 infection.

pharmacology and toxicology↗

bioRxiv2018

Signal sequences in the genome of Mononegavirales regulate the generation of copy-back defective viral genomes

Defective viral genomes of the copy-back type (cbDVGs) are the primary initiators of the antiviral immune response during infection with respiratory syncytial virus (RSV) both in vitro and in vivo. However, the mechanism governing cbDVG generation remains unknown, thereby limiting our ability to manipulate cbDVG content in order to modulate the host response to infection. Here we report a specific genomic signal that mediates the generation of RSV cbDVGs. Using a customized bioinformatics tool, we identified regions in the RSV genome frequently used to generate cbDVGs during infection. We then created a minigenome system to validate the function of one of these sequences and to determine if specific nucleotides were essential for cbDVG generation at that position. Further, we created a recombinant virus that selectively produced a specific cbDVG based on variations introduced in this sequence. The identified sequence was also found as a common site for cbDVG generation during natural RSV infections, and common cbDVGs generated at this sequence were found among samples from various infected patients. These data demonstrate that sequences encoded in the viral genome are critical determinants of the location of cbDVG generation and, therefore, this is not a stochastic process. Most importantly, these findings open the possibility of genetically manipulating cbDVG formation to modulate infection outcome. Author summaryCopy-back defective viral genomes (cbDVGs) regulate infection and pathogenesis of Mononegavirales. cbDVG are believed to arise from random errors that occur during virus replication and the predominant hypothesis is that the viral polymerase is the main driver of cbDVG generation. Here we describe a specific genomic sequence in the RSV genome that is necessary for the generation of a large proportion of the cbDVG population present during infection. We identified specific nucleotides that when modified altered cbDVG generation at this position, and we created a recombinant virus that selectively produced cbDVGs based on mutations in this sequence. These data demonstrate that the generation of RSV cbDVGs is regulated by specific viral sequences and that these sequences can be manipulated to alter the content and quality of cbDVG generated during infection.

microbiology↗

bioRxiv2018

14-3-3 recruits keratin intermediate filaments to mechanically sensitive cell-cell contacts

AbstractIntermediate filament cytoskeletal networks simultaneously support mechanical integrity and influence signal transduction pathways. Marked remodeling of the keratin intermediate filament network accompanies collective cellular morphogenetic movements that occur during early embryonic development in the frog Xenopus laevis. While this reorganization of keratin is initiated by force transduction on cell-cell contacts mediated by C-cadherin, the mechanism by which keratin filament reorganization occurs remains poorly understood. In this work we demonstrate that 14-3-3 proteins regulate keratin reorganization dynamics in embryonic mesendoderm cells from Xenopus gastrula. 14-3-3 co-localizes with keratin filaments near cell-cell junctions in migrating mesendoderm. Co-immunoprecipitation, mass spectrometry and bioinformatic analyses indicate Keratin 19 is a target of 14-3-3 in the whole embryo and, more specifically, mesendoderm tissue. Inhibition of 14-3-3 results in both the decreased exchange of keratin subunits into filaments and blocks keratin filament recruitment toward cell-cell contacts. Synthetically coupling 14-3-3 to Keratin 19 through a unique fusion construct conversely induces the localization of this keratin population to the region of cell-cell contacts. Taken together, these findings indicate that 14-3-3 acts on keratin intermediate filaments and is involved in their reorganization to sites of cell adhesion.

cell biology↗

bioRxiv2018

A Network of Networks Approach for Modeling Interconnected Brain Tissue-Specific Networks

MotivationRecent sequence-based analyses have identified a lot of gene variants that may contribute to neurogenetic disorders such as autism spectrum disorder and schizophrenia. Several state-of-the-art network-based analyses have been proposed for mechanical understanding of genetic variants in neurogenetic disorders. However, these methods were mainly designed for modeling and analyzing single networks that do not interact with or depend on other networks, and thus cannot capture the properties between interdependent systems in brain-specific tissues, circuits, and regions which are connected each other and affect behavior and cognitive processes.\n\nResultsWe introduce a novel and efficient framework, called a \"Network of Networks\" (NoN) approach, to infer the interconnectivity structure between multiple networks where the response and the predictor variables are topological information matrices of given networks. We also propose Graph-Oriented SParsE Learning (GOSPEL), a new sparse structural learning algorithm for network graph data to identify a subset of the topological information matrices of the predictors related to the response. We demonstrate on simulated data that GOSPEL outperforms existing kernel-based algorithms in terms of F-measure. On real data from human brain region-specific functional networks associated with the autism risk genes, we show that the NoN model provides insights on the autism-associated interconnectivity structure between functional interaction networks and a comprehensive understanding of the genetic basis of autism across diverse regions of the brain.\n\nAvailabilityOur software is available from https://github.com/infinite-point/GOSPEL.\n\nContactkawakubo@med.nagoya-u.ac.jp, shimamura@med.nagoya-u.ac.jp\n\nSupplementary informationSupplementary data are available at Bioinformatics online.

systems biology↗

bioRxiv2018

Potent Cas9 inhibition in bacterial and human cells by new anti-CRISPR protein families

CRISPR-Cas systems are widely used for genome engineering technologies, and in their natural setting, they play crucial roles in bacterial and archaeal adaptive immunity, protecting against phages and other mobile genetic elements. Previously we discovered bacteriophage-encoded Cas9-specific anti-CRISPR (Acr) proteins that serve as countermeasures against host bacterial immunity by inactivating their CRISPR-Cas systems1. We hypothesized that the evolutionary advantages conferred by anti-CRISPRs would drive the widespread occurrence of these proteins in nature2-4. We have identified new anti-CRISPRs using the bioinformatic approach that successfully identified previous Acr proteins1 against Neisseria meningitidis Cas9 (NmeCas9). In this work we report two novel anti-CRISPR families in strains of Haemophilus parainfluenzae and Simonsiella muelleri, both of which harbor type II-C CRISPR-Cas systems5. We characterize the type II-C Cas9 orthologs from H. parainfluenzae and S. muelleri, show that the newly identified Acrs are able to inhibit these systems, and define important features of their inhibitory mechanisms. The S. muelleri Acr is the most potent NmeCas9 inhibitor identified to date. Although inhibition of NmeCas9 by anti-CRISPRs from H. parainfluenzae and S. muelleri reveals cross-species inhibitory activity, more distantly related type II-C Cas9s are not inhibited by these proteins. The specificities of anti-CRISPRs and divergent Cas9s appear to reflect co-evolution of their strategies to combat or evade each other. Finally, we validate these new anti-CRISPR proteins as potent off-switches for Cas9 genome engineering applications.

molecular biology↗

bioRxiv2018

Single-cell level transcriptome of the maize pathogenic fungi cochliobolus heterostrophus race O in infection reveal the virulence related genes, and potential circRNA effector

Cochliobolus heterostrophus is a crucial pathogenic fungus that causes southern corn leaf blight (SCLB) in maize worldwide, however, the virulence mechanism of the dominant race O remains unclear. In this report, the single-cell level of pathogen tissue at three infection stages were collected from the host interaction-situ, and were performed next-generation sequencing from the perspectives of mRNA, circular RNA(circRNA) and long noncoding RNA(lncRNA). In the mRNA section, signal transduction, kinase, oxidoreductase, and hydrolase, et al. were significantly related in both differential expression and co-expression between virulence differential race O strains. The expression pattern of the traditional virulence factors nonribosomal peptide synthetases (NPSs), polyketide synthases (PKSs) and small secreted proteins (SSPs) were multifarious. In the noncoding RNA section, a total of 2279 circRNAs and 169 lncRNAs were acquired. Noncoding RNAs exhibited differential expression at three stages. The high virulence strain DY transcribed 450 more circRNAs than low virulence strain WF. Informatics analysis revealed numbers of circRNAs which positively correlate with race O virulence, and a cross-kingdom interaction between the pathogenic circRNA and host miRNA was predicted. An important exon-intron circRNA Che-cirC2410 combines informatics characteristics above, and highly expressed in the DY strain. Che-cirC2410 initiate from the pseudogene chhtt, which doesnt translate genetic code into protein. In-situ hybridization tells the sub-cellular localization of Che-cirC2410 include pathogen`s mycelium, periplasm, and the diseased host tissues. The target of Che-cirC2410 was predicted to be zma-miR399e-5P, and the interaction between noncoding RNAs was proved. More, the expression of zma-miR399e-5P exhibited a negative correlation to Che-cirC2410 in vivo. The deficiency of Che-circ2410 decreased the race O virulence. The host resistance to SCLB was weakened when zma-miR399e-5P was silenced. Thus, a novel circRNA-type effector and its resistance related miRNA target are proposed cautiously in this report. These findings enriched the pathogen-host dialogue by using noncoding RNAs as language, and revealed a new perspective for understanding the virulence of race O, which may provide valuable strategy of maize breeding for disease resistance.\n\nAuthor SummaryThe southern corn leaf blight (caused by Cochliobolus heterostrophus) is not optimistic in Asia, however we have limit knowledge about the infection mechanism of the dominant C.heterostrophus race O. We take full advantage of the ideal C.heterostrophus genome database, laser capture microdissection and single-cell level RNA sequencing. Hence, we could avert the artificial influence such as medium, and profile the real gene mobilization strategy in the infection. The results of coding RNA section were accessible, virulence related genes (such as the signal transduction, PKS, SSP) were detected in RNA-seq,which accord with previous reports. However, the results of noncoding RNA was astonished, 2279 circular RNAs (circRNA) and 169 long noncoding RNAs (lncRNA) were revealed in our results. Generally, the function of noncoding RNA was hypothesized in single species, but we boldly guess that the function of circRNA is rather complicated in the pathogen-host interaction. Finally, the circRNA in-situ hybridization (ISH) demonstrate the secretion of pathogen circRNA into the host tissue. By bioinformatic prediction, we found a sole microRNA target, and proved the interaction between circRNA and microRNA. These findings are likely to reveal a novel pathogen effector type: secreted circRNA.

microbiology↗

bioRxiv2018

Sequence analysis and confirmation of type IV pili-associated proteins PilY1, PilW and PilV in Acidithiobacillus thiooxidans

Acidithiobacillus thiooxidans is an acidophilic chemolithoautotrophic bacterium widely used in the mining industry due to its metabolic sulfur-oxidizing capability. The biooxidation of sulfide minerals is enhanced through the attachment of A. thiooxidans cells to the mineral surface. The Type IV pili (TfP) of At. thiooxidans may play an important role in the bacteria attachment, since among other functions, TfP play a key adhesive role in the attachment to and colonization of different surfaces. In this work, we reported for the first time the confirmed mRNA sequences of three TfP proteins from At. thiooxidans, the protein PilY1 and the TfP pilins PilW and PilV. The nucleotide sequences of these TfP proteins show changes of some nucleotide positions with respect to the corresponding annotated sequences. The bioinformatic analyses and 3D-modeling of protein structures sustain their classification as TfP proteins, as structural homologs of the corresponding proteins of P. aeruginosa, results that sustain the role of PilY1, PilW and PilV in pili assembly. Also, that PilY1 comprises the conserved Neisseria-PilC (superfamily) domain of the tip-associated adhesin, while PilW of the superfamily of putative TfP assembly proteins and PilV belongs to the superfamily of TfP assembly protein. Also, the analyses suggested the presence of specific functional domains involved in adhesion, energy transduction and signaling functions. The phylogenetic analysis indicated that the PilY1 of Acidithiobacillus genus forms a cohesive group linked with iron- and/or sulfur-oxidizing microorganisms from acid mine drainage or mine tailings. This work enriches knowledge regarding colonization, adhesion and biooxidation of inorganic sulfurs by A. thiooxidans.

microbiology↗

bioRxiv2018

An Equivariant Bayesian Convolutional Network predicts recombination hotspots and accurately resolves binding motifs

MotivationConvolutional neural networks (CNNs) have been trememdously successful in many contexts, particularly where training data is abundant and signal-to-noise ratios are large. However, when predicting noisily observed biological phenotypes from DNA sequence, each training instance is only weakly informative, and the amount of training data is often fundamentally limited, emphasizing the need for methods that make optimal use of training data and any structure inherent in the model.\n\nResultsHere we show how to combine equivariant networks, a general mathematical framework for handling exact symmetries in CNNs, with Bayesian dropout, a version of MC dropout suggested by a reinterpretation of dropout as a variational Bayesian approximation, to develop a model that exhibits exact reverse-complement symmetry and is more resistant to overtraining. We find that this model has increased power and generalizability, resulting in significantly better predictive accuracy compared to standard CNN implementations and state-of-art deep-learning-based motif finders. We use our network to predict recombination hotspots from sequence, and identify high-resolution binding motifs for the recombination-initiation protein PRDM9, which were recently validated by high-resolution assays. The network achieves a predictive accuracy comparable to that attainable by a direct assay of the H3K4me3 histone mark, a proxy for PRDM9 binding.\n\nAvailabilityhttps://github.com/luntergroup/EquivariantNetworks\n\nContactrichard.brown@well.ox.ac.uk, gerton.lunter@well.ox.ac.uk\n\nSupplementary informationSupplementary data are available at Bioinformatics online.

genomics↗

bioRxiv2018

Nitrogen regulator GlnR directly controls transcription of prpDBC operon involved in methylcitrate cycle in Mycobacterium smegmatis

Mycobacterium tuberculosis utilizes the fatty acids of the host as the carbon source. While the metabolism of odd chain fatty acids produces propionyl-CoA. Methylcitrate cycle is essential for Mycobacteria to utilize the propionyl-CoA to persist and grow on these fatty acids. In M. smegmatis, methylcitrate synthase, methylcitrate dehydratase, and methylisocitrate lyase involved in methylcitrate cycle were respectively encoded by prpC, prpD, and prpB in operon prpDBC. In this study, we found that the nitrogen regulator GlnR directly binds to the promoter region of prpDBC operon and inhibits its transcription. The typical binding sequence of GlnR was identified by bioinformatics analysis and electrophoretic mobility shift assay. The GlnR-binding motif was seperated by 164 bp with the binding site of PrpR which was a pathway-specific transcriptional activator of methylcitrate cycle. Moreover, the affinity constant of GlnR was much stronger than that of PrpR to prpDBC. The deletion of glnR resulted in poor growth in propionate or cholesterol medium comparing with wild-type strain. The {Delta}glnR mutant strain also showed a higher survival in macrophages. These results illustrated that the nitrogen regulator GlnR regulated methylcitrate cycle through directly repressing the transcription of prpDBC operon. The finding reveals an unprecedented link between nitrogen metabolism and methylcitrate pathway, and provides a potential application for controlling populations of pathogenic mycobacteria.\n\nAuthor SummaryNutrients are crucial for the survival and pathogenicity of Mycobacterium tuberculosis. The success of this pathogen survival in macrophage due to its ability to assimilate fatty acids and cholesterol from host. The cholesterol and fatty acids are catabolized via {beta}-oxidation to generate propionyl-CoA, which is then mainly metabolized via the methylcitrate cycle. The assimilation of propionyl-CoA needs to be tightly regulated to prevent its accumulation and alleviate toxicity in cell. Here, we identified a new regulator GlnR (the nitrogen transcriptional regulator) that repressed the transcription of prp operon involved in methylcitrate cycle in M. smegmatis. In this study, we found a typical GlnR binding box in prp operon, and the affinity is much stronger than that of PrpR which is known as a pathway-specific transcriptional activator of methylcitrate cycle. In addition, deletion of glnR obviously affect the growth of mutant in propionate or cholesterol medium, and show a better viability in macrophage. The findings not only provide the insights into the regulatory mechanism underlying crosstalk of nitrogen metabolism and carbon metabolism, but also reveal a potential application for controlling populations of pathogenic mycobacteria.

microbiology↗

bioRxiv2018

Over 2.5 million COI sequences in GenBank and growing

The increasing popularity of cytochrome c oxidase subunit 1 (COI) DNA metabarcoding warrants a careful look at the underlying reference databases used to make high-throughput taxonomic assignments. The objectives of this study are to document trends and assess the future usability of COI records for metabarcode identification. Over 2.5 million COI sequences were found in GenBank, half of which were fully identified to the species rank. From 2003 to 2017, the number of COI Eukaryote records deposited has grown by two orders of magnitude representing a nearly 42-fold increase in unique species. For fully identified records, 92% are at least 500 bp in length, 74% have a country annotation, and 51% have latitude-longitude annotations. To ensure the future usability of COI records in GenBank we suggest: 1) Improving the geographic representation of COI records 2) Improving the cross-referencing of COI records in the Barcode of Life Data System and GenBank to facilitate consolidation and incorporation into existing bioinformatic pipelines, 3) Adherence to the minimum information about a marker gene sequence guidelines, and 4) Integrating metabarcodes from eDNA and mixed community studies with existing sequences. COI metabarcoders are normally considered consumers of taxonomic data. Here we discuss the potential for taxonomists to reverse this pattern and instead mine metabarcode data to guide species discovery. The growth of COI reference records over the past 15 years has been substantial and is likely to be a resource across many fields for years to come.

ecology↗

bioRxiv2018

TP53 mutations promote immunogenic activity in breast cancer

BackgroundAlthough immunotherapy has recently achieved clinical successes in a variety of cancers, thus far there is no any immunotherapeutic strategy for breast cancer (BC). Thus, it is important to discover biomarkers for identifying the BC patients responsive to immunotherapy. TP53 mutations were often associated with worse clinical outcome in BC, of which the triple-negative BC (TNBC) has a high TP53 mutation rate (approximately 80%). TNBC is high-risk due to its high invasiveness, and lack of targeted therapy. To explore a potentially promising therapeutic option for the TP53-mutated BC subtype, we studied the associations between TP53 mutations and immunogenic activity in BC.\n\nMethodsWe compared enrichment levels of 26 immune gene-sets that indicated activities of diverse immune cells, functions, and pathways between TP53-mutated and TP53-wildtype BCs based on two large-scale BC multi-omics data. Moreover, we explored the molecular cues that were associated with the differences in immunogenic activity between TP53-mutated and TP53-wildtype BCs. Furthermore, we performed experimental validation of the findings from bioinformatics analysis.\n\nResultsWe found that almost all analyzed immune gene-sets had significantly higher enrichment levels in TP53-mutated BCs compared to TP53-wildtype BCs. Moreover, our experiments confirmed that mutant p53 could increase BC immunogenicity. Furthermore, our computational and experimental results showed that TP53 mutations could promote BC immunogenicity via regulation of the p53-mediated pathways including cell cycle, apoptosis, Wnt, Jak-STAT, NOD-like receptor, and glycolysis. Interestingly, we found that elevated immune activities were likely to be associated with better survival prognosis in TP53-mutated BCs, but not necessarily in TP53-wildtype BCs.\n\nConclusionsTP53 mutations promote immunogenic activity in breast cancer. This finding demonstrates a different effect of p53 dysfunction on tumor immunogenicity from that of previous studies, suggesting that the TP53 mutation status could be a useful biomarker for stratifying BC patients responsive to immunotherapy.

cancer biology↗

bioRxiv2018

Genome-wide association analysis with a 50K transcribed gene SNP-chip identifies QTL affecting muscle yield in rainbow trout

Detection of coding/functional SNPs that change the biological function of a gene may lead to identification of putative causative alleles within QTL regions and discovery of genetic markers with large effects on phenotypes. Two bioinformatics pipelines, GATK and SAMtools, were used to identify ~21K transcribed SNPs with allelic imbalances associated with important aquaculture production traits including body weight, muscle yield, muscle fat content, shear force, and whiteness in addition to resistance/susceptibility to bacterial cold-water disease (BCWD). SNPs were identified from pooled RNA-Seq data collected from ~620 fish, representing 98 families from growth- and 54 families from BCWD-selected lines with divergent phenotypes. In addition, ~29K transcribed SNPs without allelic-imbalances were strategically added to build a 50K Affymetrix SNP-chip. SNPs selected included two SNPs per gene from 14K genes and ~5K non-synonymous SNPs. The SNP-chip was used to genotype 1728 fish. The average SNP calling-rate for samples passing quality control (QC; 1,641 fish) was [≥] 98.5%. Genome-wide association (GWA) study on 878 fish (representing 197 families from 2 consecutive generations) with muscle yield phenotypes and genotyped for 35K polymorphic markers (passing QC) identified several QTL regions explaining together up to 28.40% of the additive genetic variance for muscle yield in this rainbow trout population. The most significant QTLs were on chromosomes 14 and 16 with 12.71% and 10.49% of the genetic variance, respectively. Many of the annotated genes in the QTL regions were previously reported as important regulators of muscle development and cell signaling. No major QTLs were identified in a previous GWA study using a 57K genomic SNP chip on the same fish population. These results indicate improved detection power of the transcribed gene SNP-chip in the target trait and population, allowing identification of large-effect QTLs for important traits in rainbow trout.

genomics↗

bioRxiv2018

G-quadruplex stabilization in the ions and maltose transporters inhibit Salmonella enterica growth and virulence.

The G-quadruplex structure forming motifs have recently emerged as a novel therapeutic drug target in various human pathogens. Herein, we report three highly conserved G-quadruplex motifs (SE-PGQ-1, 2, and3) in genome of all the 412 strains of Salmonella enterica. Bioinformatics analysis inferred the presence of SE-PGQ-1 in the regulatory region of mgtA, presence of SE-PGQ-2 in the open reading frame of entA and presence of SE-PGQ-3 in the promoter region of malE and malK genes. The products of mgtA and entA are involved in transport and homeostasis of Mg2+ and Fe3+ ion and thereby required for bacterial survival in the presence of reactive nitrogen/oxygen species produced by the host macrophages, whereas, malK and malE genes are involved in transport of maltose sugar, that is one of the major carbon source in the gastrointestinal tract of human. The formation of stable intramolecular G-quadruplex structures by SE-PGQs was confirmed by employing CD, EMSA and NMR spectroscopy. Cellular studies revealed the inhibitory effect of 9-amino acridine on Salmonella enterica growth. Next, CD melting analysis demonstrated the stabilizing effect of 9-amino acridine on SE-PGQs. Further, polymerase inhibition and RT-qPCR assays emphasize the biological relevance of predicted G-quadruplex in the expression of PGQ possessing genes and demonstrate the G-quadruplexes as a potential drug target for the devolping novel therapeutics for combating Salmonella enterica infection.\n\nAuthor SummarySince last several decades scientific community has witnessed a rapid increase in number of such human pathogenic bacterial species that acquired resistant to multiple antibacterial agents. Currently, emergence of multidrug-resistant strains remain a major public health concern for clinical investigators that rings a global alarm to search for novel and highly conserved drug targets. Recently, G-quadruplex structure forming nucleic acid sequences were endorsed as highly conserved Drug target for preventing infection of several human pathogens including viral and protozoan species. Therefore, here we explored the presence G-quadruplex forming motif in genome of Salmonella enterica bacteria that causes food poisoning, and enteric fever in human. The formation of intra molecular G-quadruplex structure in four genes (mgtA, entA, malE and malK) was confirmed by NMR, CD and EMSA. The 9-amino acridine, a known G-quadruplex binder has been shown to stabilize the predicted G-quadruplex motif and decreases the expressioin of G-quadruplex hourbouring genes using RT-PCR and cellular toxicity assay. This study concludes the presence of G-quadruplex motifs in essential genes of Salmonella enterica genome as a novel and conserved drug target and 9-amino acridine as candidate small molecule for preventing the infection of Salmonella enterica using a G4 mediated inhibition mechanism.

genomics↗

bioRxiv2018

Identification of circulating protein biomarkers for pancreatic cancer cachexia

BackgroundOver 80% of patients with pancreatic ductal adenocarcinoma (PDAC) suffer from cachexia, characterized by severe muscle and fat loss. Although various model systems have improved our understanding of cachexia, translating the findings to human cachexia has remained a challenge. In this study, our objectives were to i) identify circulating protein biomarkers using serum for human PDAC cachexia, (ii) identify the ontological functions of the identified biomarkers and (iii) identify new pathways associated with human PDAC cachexia by performing protein co-expression analysis.\n\nMethodsSerum from 30 patients with PDAC was collected. Body composition measurements of skeletal muscle index (SMI), skeletal muscle density (SMD), total adipose index (TAI) were obtained from computed tomography scans (CT). Cancer associated weight loss (CAWL), an ordinal classification of history of weight loss and body mass index (BMI) was obtained from medical record. Serum protein profiles and concentrations were generated using SOMAscan, a quantitative aptamer-based assay. Ontological analysis of the proteins correlated with clinical variables (r[≥] 0.5 and p<0.05) was performed using DAVID Bioinformatics. Protein co-expression analysis was determined using pairwise Spearmans correlation.\n\nResultsOverall, 111 proteins of 1298 correlated with these clinical measures, 48 proteins for CAWL, 19 for SMI, 14 for SMD, and 30 for TAI. LYVE1, a homolog of CD44 implicated in tumor metastasis, was the top CAWL-associated protein (r= 0.67, p=0.0001). Other proteins such as INHBA, MSTN/GDF11, and PIK3R1 strongly correlated with CAWL. Proteins correlated with cachexia included those associated with proteolysis, acute inflammatory response, as well as B cell and T cell activation. Protein co-expression analysis identified networks such as activation of immune related pathways such as B-cell signaling, Th1 and Th2 pathways, natural killer cell signaling, IL6 signaling, and mitochondrial dysfunction.\n\nConclusionTaken together, these data both identify immune system molecules and additional secreted factors and pathways not previously associated with PDAC and confirm the activation of previously identified pathways. Identifying altered secreted factors in serum of PDAC patients may assist in developing minimally invasive laboratory tests for clinical cachexia as well as identifying new mediators.

cancer biology↗