Biology subjects

Roy, S.

Publications and source records attributed to Roy, S..

At least 289 records · Page 16Linked to original sources

bioRxiv2020

Live imaging of breast tumors shows macrophage-dependent induction and TMEM-mediated enrichment of cancer stem cells during metastatic dissemination

Cancer stem cells (CSCs) play an important role during metastasis, but the dynamic behavior and induction mechanisms of CSCs are not well understood. We employed high-resolution intravital microscopy using a CSC biosensor to directly observe CSCs in live mice with mammary tumors. CSCs display the slow-migratory, invadopod-rich phenotype that is the hallmark of disseminating tumor cells. CSCs are enriched near macrophages, particularly near macrophage-containing intravasation sites called Tumor Microenvironment of Metastasis (TMEM) doorways. A dramatic enrichment of CSCs occurs on association with TMEM doorways, contributing to the finding that CSCs represent [~]>60% of circulating tumor cells. Mechanistically, stemness is induced in non-stem cancer cells upon their direct contact with macrophages via Notch signaling. In breast cancers from patients, the density of TMEM doorways correlates strongly with the proportion of cancer cells expressing stem cell markers, indicating that in human breast cancer TMEM doorways are not only cancer cell intravasation portals but also CSC programming sites. One Sentence SummaryIntravital imaging reveals macrophage-mediated induction of cancer stem cells in vivo and their dramatic enrichment on dissemination through TMEM doorways.

cancer biology↗

bioRxiv2020

Efficient production of Moloney murine leukemia virus-like particles pseudotyped with the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) spike protein

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) outbreak that started in China at the end of 2019 has rapidly spread to become pandemic. Several investigational vaccines that have already been tested in animals and humans were able to induce neutralizing antibodies against the SARS-CoV-2 spike (S) protein, however protection and long-term efficacy in humans remain to be demonstrated. We have investigated if a virus-like particle (VLP) derived from Moloney murine leukemia virus (MLV) could be engineered to become a candidate SARS-CoV-2 vaccine amenable to mass production. First, we showed that a codon optimized version of the S protein could migrate efficiently to the cell membrane. However, efficient production of infectious viral particles was only achieved with stable expression of a shorter version of S in its C-terminal domain ({Delta}S) in 293 cells that express MLV Gag-Pol (293GP). The incorporation of {Delta}S was 15-times more efficient into VLPs as compared to the full-length version, and that was not due to steric interference between the S cytoplasmic tail and the MLV capsid. Indeed, a similar result was also observed with extracellular vesicles released from parental 293 and 293GP cells. The amount of {Delta}S incorporated into VLPs released from producer cells was robust, with an estimated 1.25 g/ml S2 equivalent (S is comprised of S1 and S2). Thus, a scalable platform that has the potential for production of pan-coronavirus VLP vaccines has been established. The resulting nanoparticles could potentially be used alone or as a boost for other immunization strategies for COVID-19. IMPORTANCESeveral candidate COVID-19 vaccines have already been tested in humans, but their protective effect and long-term efficacy are uncertain. Therefore, it is necessary to continue developing new vaccine strategies that could be more potent and/or that would be easier to manufacture in large-scale. Virus-like particle (VLP) vaccines are considered highly immunogenic and have been successfully developed for human papilloma virus as well as hepatitis and influenza viruses. In this study, we report the generation of a robust Moloney murine leukemia virus platform that produces VLPs containing the spike of SARS-CoV-2. This vaccine platform that is compatible with lyophilization could simplify storage and distribution logistics immensely.

microbiology↗

bioRxiv2020

Polygenic mutations model the pleiotropic disease of Fanconi Anemia

Fanconi Anemia (FA) is a prototypic genetic disease signified by heterogeneous phenotypes including cancer, bone marrow failure, short stature, congenital abnormalities, infertility, sub-mendelian birth rate, genome instability and high cellular sensitivity to cancer therapeutics1-4. Clinical diagnosis is confirmed by identifying biallelic, homo- or hemizygous mutations in any one of twenty-three FANC genes1,5. Puzzlingly, inactivation of one single Fanc gene in mice fails to faithfully model the human disease manifestations6-8. We here delineate a preclinical Fanc mouse model with mutations in two genes, Fancd1/Brca2 and Fanco/Rad51c, that recapitulates the severity and heterogeneity of the human disease manifestations including death by cancer at young age. Surprisingly, these grave phenotypes cannot be explained by the sum of phenotypes seen in mice with single gene inactivation, which are unremarkable. In contrast to expectations from classic epistasis analysis of genetic pathways, the data instead reveal an unexpected functional synergism of polygenic Fanc mutations. Importantly in humans, whole exome sequencing uncovers that FANC co-mutation in addition to the identified inactivating FANC gene mutation is a frequent event in FA patients. Collectively, the data establish a concept of polygenic stress as an important contributor to disease manifestations, with implications for molecular diagnostics.

cancer biology↗

bioRxiv2020

The Molecular Landscape of the Aging Mouse Liver

Systems biology approaches often use inferred networks of gene expression and metabolite data to identify regulatory factors and pathways connected with phenotypic variance. Generally, study-specific multi-layer "Omics" datasets are used to contextualize generic molecular networks. In this regard separating upstream causal mechanisms, downstream biomarkers, and incidental correlations remains a significant challenge, yet it is essential for designing mechanistic experiments. To address this, we designed a study following a population of 2157 individuals from 89 isogenic BXD mouse strains across their lifespan to identify molecular interactions among genotype, environment, age (GxExA) and metabolic fitness. Each strain was separated into two cohorts, one fed low fat (6% cal/fat) and the other high fat (60% cal/fat) diets. Tissues were collected for 662 individuals (309 cohorts) diverging across age (7, 12, 18, and 24 months), diet, sex, and strain. Transcriptome, proteome, and metabolome data were generated for liver. Of these we identified linear relations among these molecular data with lifespan for the same genomes of mice (Roy et al. 2020), and we defined [~]1100 novel protein-coding genes associated with longevity. We knocked down the ortholog of Ctsd in C. elegans. The treatment reduced longevity both in wildtype and in mutant long-lived strains, thus validating the prediction. Next, to assess the molecular impact of GxExA on gene expression, the multi-omics data was parsed into metabolic networks where connectivity varied due to the independent variables. Differences in edge strengths connecting nodes in these molecular networks according to each variable enabled causal inference by using stability selection, with roughly 21% of novel gene-pathway connections being causally affected by diet and/or age. For instance, Chchd2 is activated by aging and drives changes in the proteasome, oxidative phosphorylation, and mitochondrial translation transcriptional networks. Together, we have developed a large multi-omics resource for studying aging in the liver, and a resource for turning standard associations into causal networks.

systems biology↗

bioRxiv2020

Graph-regularized matrix factorization for reliable detection of topological units from high-throughput chromosome conformation capture datasets

The three-dimensional (3D) organization of the genome plays a critical role in gene regulation for diverse normal and disease processes. High-throughput chromosome conformation capture (3C) assays, such as Hi-C, SPRITE, GAM, and HiChIP, have revealed higher-order organizational units such as topologically associating domains (TADs), which can shape the regulatory landscape governing downstream phenotypes. Analysis of high-throughput 3C data depends on the sequencing depth, which directly affects the resolution and the sparsity of the generated 3D contact count map. Identification of TADs remains a significant challenge due to the sensitivity of existing methods to resolution and sparsity. Here we present GRiNCH, a novel matrix-factorization-based approach for simultaneous TAD discovery and smoothing of contact count matrices from high-throughput 3C data. GRiNCH TADs are enriched in known architectural proteins and chromatin modification signals and are stable to the resolution, and sparsity of the input data. GRiNCH smoothing improves the recovery of structure and significant interactions from low-depth datasets. Furthermore, enrichment analysis of 746 transcription factor motifs in GRiNCH TADs from developmental time-course and cell-line Hi-C datasets predicted transcription factors with potentially novel genome organization roles. GRiNCH is a broadly applicable tool for the analysis of high throughput 3C datasets from a variety of platforms including SPRITE and HiChIP to understand 3D genome organization in diverse biological contexts.

bioinformatics↗

bioRxiv2020

Receptor tyrosine kinases activate heterotrimeric G proteins via phosphorylation within the interdomain cleft of Gαi

The molecular mechanisms by which receptor tyrosine kinases (RTKs) and heterotrimeric G proteins, two major signaling hubs in eukaryotes, independently relay signals across the plasma membrane have been extensively characterized. How these hubs crosstalk has been a long-standing question, but answers remain elusive. Using linear-ion-trap mass spectrometry in combination with biochemical, cellular, and computational approaches, we unravel a mechanism of activation of heterotrimeric G proteins by RTKs and chart the key steps that mediate such activation. Upon growth factor stimulation, the guanine-nucleotide exchange modulator, GIV, dissociates Gi*{beta}{gamma} trimers, scaffolds monomeric Gi with RTKs, and facilitates the phosphorylation on two tyrosines located within the inter-domain cleft of Gi. Phosphorylation triggers the activation of Gi and inhibits second messengers (cAMP). Tumor-associated mutants reveal how constitutive activation of this pathway impacts cells decision to go vs. grow. These insights define a tyrosine-based G protein signaling paradigm and reveal its importance in eukaryotes. Significance StatementGrowth factors and heterotrimeric G proteins are two of the most widely studied signaling pathways in eukaryotes; their crosstalk shapes some of the most fundamental cellular responses in both health and disease. Although mechanisms by which G protein pathways transactivate growth factor RTKs has been well-defined, how the reverse may happen is less understood. This study defines the key steps and cellular consequences of a fundamental mechanism of signal crosstalk that enables RTKs to transactivate heterotrimeric G protein, Gi. Mutations found in tumors shed light on how derailing this mechanism impacts tumor cell behavior. Thus, findings not only show how cells integrate extracellular signals via pathway crosstalk, but also demonstrate the relevance of this pathway in cancers.

biochemistry↗

bioRxiv2020

Dynamics of the COVID -19 Related Publications

BackgroundThis study aims to analyze the dynamics of the published articles and preprints of Covid-19 related literature from different scientific databases and sharing platforms. MethodsThe PubMed, Elsevier, and Research Gate (RG) databases were under consideration in this study over a specific time. Analyses were carried out on the number of publications as (a) function of time (day), (b) journals and (c) authors. Doubling time of the number of publications was analyzed for PubMed "all articles" and Elsevier published articles. Analyzed databases were (1A) PubMed "all articles" (01/12/2019-12/06/2020) (1B) PubMed Review articles (01/12/2019-2/5/2020) and (1C) PubMed Clinical Trials (01/01/2020-30/06/2020) (2) Elsevier all publications (01/12/2019-25/05/2020) (3) RG (Article, Pre Print, Technical Report) (15/04/2020-30/4/2020). FindingsTotal publications in the observation period for PubMed, Elsevier, and RG were 23000, 5898 and 5393 respectively. The average number of publications/day for PubMed, Elsevier and RG were 70.0 {+/-}128.6, 77.6{+/-}125.3 and 255.6{+/-}205.8 respectively. PubMed shows an avalanche in the number of publication around May 10, number of publications jumped from 6.0{+/-}8.4/day to 282.5{+/-}110.3/day. The average doubling time for PubMed, Elsevier, and RG was 10.3{+/-}4 days, 20.6 days, and 2.3{+/-}2.0 days respectively. In PubMed average articles/journal was 5.2{+/-}10.3 and top 20 authors representing 935 articles are of Chinese descent. The average number of publications per author for PubMed, Elsevier, and RG was 1.2{+/-}1.4, 1.3{+/-}0.9, and 1.1{+/-}0.4 respectively. Subgroup analysis, PubMed review articles mean and median review time for each article were <0|17{+/-}17|77> and 13.9 days respectively; and reducing at a rate of-0.21 days (count)/day. InterpretationAlthough the disease has been known for around 6 months, the number of publications related to the Covid-19 until now is huge and growing very fast with time. It is essential to rationalize the publications scientifically by the researchers, authors, reviewers, and publishing houses. FundingNone

scientific communication and education↗

bioRxiv2020

Impact Analysis of SARS-CoV2 on Signaling Pathways during COVID19 Pathogenesis using Codon Usage Assisted Host-Viral Protein Interactions

Understanding the molecular mechanism of COVID19 disease pathogenesis helps in the rapid development of therapeutic targets. Usually, viral protein targets host proteins in an organized fashion. The pathogen may target cell signaling pathways to disrupt the pathway genes regular activities, resulting in disease. Understanding the interaction mechanism of viral and host proteins involved in different signaling pathways may help decipher the attacking mechanism on the signal transmission during diseases, followed by discovering appropriate therapeutic solutions. The expression of any viral gene depends mostly on the host translational machinery. Recent studies report the great significance of codon usage biases in establishing host-viral protein-protein interactions (PPI). Exploiting the codon usage patterns between a pair of co-evolved host and viral proteins may present novel insight into the host-viral protein interactomes during disease pathogenesis. Leveraging the codon usage pattern similarity (and dissimilarity), we propose a computational scheme to recreate the hostviral protein interaction network (HVPPI). We use seventeen (17) essential signaling pathways for our current work and study the possible targeting mechanism of SARS-CoV2 viral proteins on such pathway proteins. We infer both negatively and positively interacting edges in the network. We can find a relationship where one host protein may target by more than one viral protein. Extensive analysis performed to understand the network topologically and the attacking behavior of the viral proteins. Our study reveals that viral proteins, mostly utilize codons, rare in the targeted host proteins (negatively correlated interaction). Among non-structural proteins, NSP3 and structural protein, Spike (S) protein, are the most influential proteins in interacting multiple host proteins. In ranking the most affected pathways, MAPK pathways observe to be worst affected during the COVID-19 disease. A good number of targeted proteins are highly central in host protein interaction networks. Proteins participating in multiple pathways are also highly connected in their own PPI and mostly targeted by multiple viral proteins.

bioinformatics↗

bioRxiv2020

Comparative Analysis of Human Coronaviruses Focusing on Nucleotide Variability and Synonymous Codon Usage Pattern

Prevailing pandemic across the world due to SARSCoV-2 drawing great attention towards discovering its evolutionary origin. We perform an exploratory study to understand the variability of the whole coding region of possible proximal evolutionary neighbours of SARSCoV-2. We consider seven (07) human coronavirus strains from six different species as a candidate for our study. First, we observe a good variability of nucleotides across candidate strains. We did not find a significant variation of GC content across the strains for codon position first and second. However, we interestingly see huge variability of GC-content in codon position 3rd (GC3), and pairwise mean GC-content (SARSCoV, MERSCoV), and (SARSCoV-2, hCoV229E) are quite closer. While observing the relative abundance of dinucleotide feature, we find a shared typical genetic pattern, i.e., high usage of GC and CT nucleotide pair at the first two positions (P12) of codons and the last two positions (P23) of codons, respectively. We also observe a low abundance of CG pair that might help in their evolution bio-process. Secondly, Considering RSCU score, we find a substantial similarity for mild class coronaviruses, i.e., hCoVOC43, hCoVHKU1, and hCoVNL63 based on their codon hit with high RSCU value ([≥] 1.5), and minim number of codons hit (count-9) is observed for MERSCoV. We see seven codons ATT, ACT, TCT, CCT, GTT, GCT and GGT with high RSCU value, which are common in all seven strains. These codons are mostly from Aliphatic and Hydroxyl amino acid group. A phylogenetic tree built using RSCU feature reveals proximity among hCoVOC43 and hCoV229E (mild). Thirdly, we perform linear regression analysis among GC content in different codon position and ENC value. We observe a strong correlation (significant p-value) between GC2 and GC3 for SARSCoV-2, hCoV229E and hCoVNL63, and between GC1 and GC3 for hCoV229E, hCoVNL63, SARSCoV. We believe that our findings will help in understanding the mechanism of human coronavirus.

genomics↗

bioRxiv2020

Dynamic regulatory module networks for inference of cell type specific transcriptional networks

Multi-omic datasets with parallel transcriptomic and epigenomic measurements across time or cell types are becoming increasingly common. However, integrating these data to infer regulatory network dynamics is a major challenge. We present Dynamic Regulatory Module Networks (DRMNs), a novel approach that uses multi-task learning to infer cell type-specific cis-regulatory networks dynamics. Compared to existing approaches, DRMN integrates expression, chromatin state and accessibility, accurately predicts cis-regulators of context-specific expression and models network dynamics across linearly and hierarchically related contexts. We apply DRMN to three dynamic processes of different experimental designs and predict known and novel regulators driving cell type-specific expression patterns.

bioinformatics↗

bioRxiv2020

A multiple ion-uptake phenotyping platform reveals shared mechanisms that affect nutrient uptake by maize roots

Nutrient uptake is critical for crop growth and determined by root foraging in soil. Growth and branching of roots lead to effective root placement to acquire nutrients, but relatively less is known about absorption of nutrients at the root surface from the soil solution. This knowledge gap could be alleviated by understanding sources of genetic variation for short-term nutrient uptake on a root length basis. A new modular platform for high-throughput phenotyping of multiple ion uptake kinetics was designed to determine nutrient uptake rates in Zea mays. Using this system, uptake rates were characterized for the crop macronutrients nitrate, ammonium, potassium, phosphate and sulfate among the Nested Association Mapping (NAM) population founder lines. The data revealed that substantial genetic variation exists for multiple ion uptake rates in maize. Interestingly, specific nutrient uptake rates (nutrient uptake rate per length of root) were found to be both heritable and distinct from total uptake and plant size. The specific uptake rates of each nutrient were positively correlated with one another and with specific root respiration (root respiration rate per length of root), indicating that uptake is governed by shared mechanisms. We selected maize lines with high and low specific uptake rates and performed an RNA-seq analysis, which identified key regulatory components involved in nutrient uptake. The high-throughput multiple ion uptake kinetics pipeline will help further our understanding of nutrient uptake, parameterize holistic plant models, and identify breeding targets for crops with more efficient nutrient acquisition. Significance StatementNutrient uptake is among the most limiting factors for plant growth and yet has not been used as a selection criterion in breeding. This is partly due to the lack of high-throughput phenotyping methods for measuring nutrient uptake. Here we describe a novel high-throughput phenotyping pipeline for quantification of multiple ion uptake rates. Using this new phenotyping system, our results demonstrate that specific ion uptake performance by maize plants is positively correlated among the macronutrients nitrogen, phosphorus, potassium and sulfur, and that substantial variation exists within a genetically diverse population. The findings reveal components of regulatory pathways possibly related with enhanced uptake, and confirm that nutrient uptake itself is a potential target for breeding of nutrient-efficient crops.

plant biology↗

bioRxiv2020

Denitrification kinetics indicates nitrous oxide uptake is unaffected by electron competition in Accumulibacter

Denitrifying phosphorus removal is a cost and energy efficient treatment technology that relies on polyphosphate accumulating organisms (DPAOs) utilizing nitrate or nitrite as terminal electron acceptor. Denitrification is a multistep process and many organisms do not possess the complete pathway, leading to the accumulation of intermediates such as nitrous oxide (N2O), a potent greenhouse gas and ozone depleting substance. Candidatus Accumulibacter organisms are prevalent in denitrifying phosphorus removal processes and, according to genomic analyses, appear to vary in their denitrification abilities based on their lineage. Yet, denitrification kinetics and nitrous oxide accumulation by Accumulibacter after long-term exposure to either nitrate or nitrite as electron acceptor have never been compared. We investigated the preferential use of the nitrogen oxides involved in denitrification and nitrous oxide accumulation in two enrichments of Accumulibacter and a competitor - the glycogen accumulating organism Candidatus Competibacter. A metabolic model was modified to predict phosphorus removal and denitrification rates when nitrate, nitrite or N2O were added as electron acceptors in different combinations. Unlike previous studies, no N2O accumulation was observed for Accumulibacter in the presence of multiple electron acceptors. Electron competition did not affect denitrification kinetics or N2O accumulation in Accumulibacter or Competibacter. Despite the presence of sufficient internal storage polymers (polyhydroxyalkanoates, or PHA) as energy source for each denitrification step, the extent of denitrification observed was dependent on the dominant organism in the enrichment. Accumulibacter showed complete denitrification and N2O utilization, whereas for Competibacter denitrification was limited to reduction of nitrate to nitrite. These findings indicate that DPAOs can contribute to lowering N2O emissions in the presence of multiple electron acceptors under partial nitritation conditions.

bioengineering↗

bioRxiv2020

Disulfide reduction allosterically destabilizes the β-ladder sub-domain assembly within the NS1 dimer of ZIKV

The Zika virus (ZIKV) was responsible for a recent debilitating epidemic that till date has no cure. A potential way to reduce ZIKV virulence is to limit the action of the non-structural proteins involved in its viral replication. One such protein, NS1, encoded as a monomer by the viral genome, plays a major role via symmetric oligomerization. We examine the homodimeric structure of the dominant {beta}-ladder segment of NS1 with extensive all atom molecular dynamics. We find it stably bounded by two spatially separated interaction clusters (C1 and C2) with significant differences in the nature of their interactions. Four pairs of distal, intra-monomeric disulfide bonds are found to be coupled to the stability, local structure, and wettability of the interfacial region. Symmetric reduction of the intra-monomeric disulfides triggers marked dynamical heterogeneity, interfacial wettability and asymmetric salt bridging propensity. Harnessing the model-free Lipari-Szabo based formalism for estimation of conformational entropy (Sconf), we find clear signatures of heterogeneity in the monomeric conformational entropies. The observed asymmetry, very small in the unperturbed state, expands significantly in the reduced states. This allosteric effect is most noticeable in the electrostatically bound C2 cluster that underlies the greatest stability in the unperturbed state. Allosteric induction of conformational and thermodynamic asymmetry is expected to affect the pathways leading to symmetric higher ordered oligomerization, and thereby affect crucial replication pathways. Statement of significanceControlling viral pathogenesis remains a challenge in the face of modern-day epidemics. Though cumbersome and fraught with misleads, most therapeutic endeavors lean towards the design of drug molecules targeting specific proteins involved in viral pathogenesis. This work demonstrates an alternative approach, namely the usage of allosteric intervention to disrupt the binding integrity of the primary domain of the non-structural NS1 protein dimer crucially important in ZIKV virulence. The intervention, triggered by symmetric reduction of the internal monomeric disulfide bonds, results in weakening and distortion of the distal binding interfaces. It further introduces marked structural and entropic asymmetry within the homooligomeric unit, precluding the formation of higher ordered oligomers of high symmetry. The results have important ramifications for consolidated efforts at limiting ZIKV virulence.

biophysics↗

bioRxiv2020

SARS-CoV-2 genomes recovered by long amplicon tiling multiplex approach using nanopore sequencing and applicable to other sequencing platforms

Genomic surveillance has become a useful tool for better understanding virus pathogenicity, origin and spread. Obtaining accurately assembled, complete viral genomes directly from clinical samples is still a challenging. Here, we describe three protocols using a unique primer set designed to recover long reads of SARS-CoV-2 directly from total RNA extracted from clinical samples. This protocol is useful, accessible and adaptable to laboratories with varying resources and access to distinct sequencing methods: Nanopore, Illumina and/or Sanger.

molecular biology↗

bioRxiv2020

Dynamical asymmetry exposes 2019-nCoV prefusion spike

The novel coronavirus (2019-nCoV) spike protein is a smart molecular machine that instigates the entry of coronavirus to the host cell causing the COVID-19 pandemic. In this study, a structural-topology based model Hamiltonian of C3 symmetric trimeric spike is developed to explore its complete conformational energy landscape using molecular dynamic simulations. The study finds 2019-nCoV to adopt a unique strategy by undertaking a dynamic conformational asymmetry induced by a few unique inter-chain interactions. This results in two prevalent asymmetric structures of spike where one or two spike heads lifted up undergoing a dynamic transition likely to enhance rapid recognition of the host-cell receptor turning on its high-infectivity. The crucial interactions identified in this study are anticipated to potentially affect the efficacy of therapeutic targets. One Sentence SummaryInter-chain-interaction driven rapid symmetry breaking strategy adopted by the prefusion trimeric spike protein likely to make 2019-nCoV highly infective.

biophysics↗

bioRxiv2020

Access to Scientific Literature by the Conservation Community

Access to the scientific literature is perceived to be a challenge to the biodiversity conservation community, but actual level of literature access relative to needs has never been assessed globally. We examined this question by surveying the constituency of the International Union for Conservation of Nature (IUCN) as a proxy for the conservation community, generating 2,285 responses. Of these respondents, ∼97% need to use the scientific literature in order to support their IUCN-related conservation work, with ∼50% needing to do so at least once per week. The crux of the survey revolved around the question, “How easy is it for you currently to obtain the scientific literature you need to carry out your IUCN-related work?” and revealed that roughly half (49%) of the respondents find it not easy or not at all easy to access scientific literature. We fitted a binary logistic regression model to explore factors predicting ease of literature access. Whether the respondent had institutional literature access (55% do) is the strongest predictor, with region (Western Europe, the United States, Canada, Australia and New Zealand) and gender (male) also significant predictors. Approximately 60% of respondents from Western Europe, the United States, Canada, Australia and New Zealand have institutional access compared to ∼50% in Asia and Latin America, and ∼40% in Eastern Europe and in Africa. Nevertheless, accessing free online material is a popular means of accessing literature for both those with and without institutional access. The four journals most frequently mentioned when asked which journal access would deliver the greatest improvements to the respondent’s IUCN-related work were Conservation Biology, Biological Conservation, Nature, and Science. The majority prefer to read journal articles on screen but prefer to read books in hard copy. Overall, it is apparent that access to the literature is a challenge facing roughly half of the conservation community worldwide.View Full Text

scientific communication and education↗

bioRxiv2020

Antimicrobial Resistance Profile and mcr-1 gene Detection in Salmonella Isolates from Poultry in Bangladesh: Molecular and Bioinformatics Characterization

Antimicrobial resistance gene mcr-1 has been disseminated globally since its first discovery in Southern China in late 2015. However, the mcr-1 gene had not been identified previously in Salmonella isolates from poultry in Bangladesh. Here, we aimed to explore antimicrobial resistance gene mcr-1 in Salmonella isolates. Eighty two Salmonella isolates were isolated and characterized from suspected poultry specimens received from different zones of the country. A phenotypic disc diffusion assay with 15 antimicrobial agents was performed following CLSI standard. The disk diffusion assay showed that, all of the isolates presented high resistance to colistin (92.68%), oxytetracycline (86.59%), co-trimoxazole (76.83%), ciprofloxacin (73.17%) and enrofloxacin (65.85%). Further, randomly selected 10 Salmonella isolates were analyzed by polymerase chain reaction (PCR) targeting genus-specific invA and antimicrobial (colistin) resistance mcr-1 genes. Five were confirmed for the presence of the mcr-1 gene belonging to Salmonella spp. Further, sequencing followed by phylogenetic analysis revealed divergent evolutionary relation between the LptA and MCR proteins rendering them resistant to colistin. Three-dimensional homology structures of MCR-1 proteins were constructed and verified using different bioinformatics tools. Moreover, molecular docking interactions suggested that, MCR-1 and LptA share a similar substrate binding cavity which could be validated for the functional analysis. The results represent here is the first molecular and in silico analysis of colistin resistance mcr-1 gene of Salmonella in poultry in Bangladesh, which may emphasize the importance of the study on antibiotic resistance genes requiring for national monitoring and strategic surveillance in the country.

microbiology↗

bioRxiv2020

Analysis procedures for assessing recovery of high quality, complete, closed genomes from Nanopore long read metagenome sequencing

New long read sequencing technologies offer huge potential for effective recovery of complete, closed genomes from complex microbial communities. Using long read (MinION) obtained from an ensemble of activated sludge enrichment bioreactors, we 1) describe new methods for validating long read assembled genomes using their counterpart short read metagenome assembled genomes; 2) assess the influence of different correction procedures on genome quality and predicted gene quality and 3) contribute 21 new closed or complete genomes of community members, including several species known to play key functional roles in wastewater bioprocesses: specifically microbes known to exhibit the polyphosphate- and glycogen-accumulating organism phenotypes (namely Accumulibacter and Dechloromonas, and Micropruina and Defluviicoccus, respectively), and filamentous bacteria (Thiothrix) associated with the formation and stability of activated sludge flocs. Our findings further establish the feasibility of long read metagenome-assembled genome recovery, and demonstrate the utility of parallel sampling of moderately complex enrichments communities for recovery of genomes of key functional species relevant for the study of complex wastewater treatment bioprocesses.

bioinformatics↗