Biology subjects

Ahmed, S.

Publications and source records attributed to Ahmed, S..

At least 127 records · Page 7Linked to original sources

bioRxiv2020

Heterochromatin Replication: Direct Interaction of DNA replication machinery with heterochromatin code writer Clr4/Suv39 and reader Swi6/HP1 in S. pombe

The establishment of heterochromatin in fission yeast involves methyltransferase Clr4-mediated H3-Lys9 methylation, which is bound specifically by Swi6/HP1. However, the mechanism of propagation of heterochromatin through multiple cell divisions is not known. A role of DNA replication in propagating the heterochromatin is envisaged. Studies in S. pombe have indicated a direct interaction between DNA Pol and Swi6/HP1 and between DNA Pol{varepsilon} and Rik1-Dos2 complex, suggesting a coupling between DNA replication and heterochromatin assembly. Here, we show that like DNA Pol, Pol{delta}, which plays a role in both leading and lagging strand replication, also plays a role in silencing at mating type and centromere. We show that both the polymerases and {delta} interact directly with both Clr4 and Swi6/HP1. Mutations in both the polymerases lead to decrease in H3-Lys9 methylation and Swi6 at the mating type and left outer repeats of centromeres I and II, with a reciprocal increase in their level at the central element, cnt, at all the three centromeres. These mutations also cause defects in chromosome segregation, recruitment of Cohesin and chromosome dynamics during mitosis and meiosis. Thus, our results indicate that a tight coordination between DNA replication machinery and propagation of the heterochromatin-specific epigenetic mark.

genetics↗

bioRxiv2020

ACP-MHCNN: An Accurate Multi-Headed Deep-Convolutional Neural Network to Predict Anticancer peptides

Although advancing the therapeutic alternatives for treating deadly cancers has gained much attention globally, still the primary methods such as chemotherapy have significant downsides and low specificity. Most recently, Anticancer peptides (ACPs) have emerged as a potential alternative to therapeutic alternatives with much fewer negative side-effects. However, the identification of ACPs through wet-lab experiments is expensive and time-consuming. Hence, computational methods have emerged as viable alternatives. During the past few years, several computational ACP identification techniques using hand-engineered features have been proposed to solve this problem. In this study, we propose a new multi headed deep convolutional neural network model called ACP-MHCNN, for extracting and combining discriminative features from different information sources in an interactive way. Our model extracts sequence, physicochemical, and evolutionary based features for ACP identification through simultaneous interaction with different numerical peptide representations while restraining parameter overhead. It is evident through rigorous experiments using cross-validation and independent-dataset that ACP-MHCNN outperforms other models for anticancer peptide identification by a substantial margin. ACP-MHCNN outperforms state-of-the-art model by 6.3%, 8.6%, 3.7%, 4.0%, and 0.20 in terms of accuracy, sensitivity, specificity, precision, and MCC respectively. ACP-MHCNN and its relevant codes and datasets are publicly available at: https://github.com/mrzResearchArena/Anticancer-Peptides-CNN.

bioinformatics↗

bioRxiv2020

Elicitation of potent serum neutralizing antibody responses in rabbits by immunization with an HIV-1 clade C trimeric Env derived from an Indian elite neutralizer

Evaluating the structure-function relationship of viral envelope (Env) evolution and the development of broadly cross-neutralizing antibodies (bnAbs) in natural infection can inform rational immunogen design. In the present study, we examined the magnitude and specificity of autologous neutralizing antibodies induced in rabbits by a novel HIV-1 clade C Env protein (1PGE-THIVC) vis-a-vis those developed in an elite neutralizer from whom the env sequence was obtained that was used to prepare the soluble Env protein. The thermostable 1PGE-THIVC Env displayed a native like pre-fusion closed conformation in solution as determined by small angle X-ray scattering (SAXS) and negative stain electron microscopy (EM). This closed spike conformation of 1PGE-THIVC Env trimers was correlated with weak or undetectable binding of non-neutralizing monoclonal antibodies (mAbs) compared to neutralizing mAbs. Furthermore, 1PGE-THIVC SOSIP induced potent neutralizing antibodies in rabbits to autologous virus variants. The autologous neutralizing antibody specificity induced in rabbits by 1PGE-THIVC was mapped to the C3/V4 region (T362/P401) of viral Env. This observation agreed with electron microscopy polyclonal epitope mapping (EMPEM) of the Env trimer complexed with IgG Fab prepared from the immunized rabbit sera. While the specificity of antibodies elicited in rabbits associated with neutralizing autologous viruses were distinct to those developed in the elite neutralizer, EMPEM analysis demonstrated significant changes to Env conformations when incubated with polyclonal antibody sera from the elite neutralizer, suggesting these antibodies lead to the destabilization of Env trimers. Our study not only shows distinct mechanisms associated with potent neutralization of sequence matched and unmatched autologous viruses by antibodies induced in rabbits and in the elite neutralizer, but also highlights how neutralizing antibodies developed during the course of natural infection can impact viral Env conformations. Author SummaryThe interplay between circulating virus variants and broadly cross neutralizing polyclonal antibodies developed in a subset of elite neutralizers is widely believed to provide strategies for rational immunogen design. In the present study, we studied the structural, antigenic and immunogenic properties of a thermostable soluble trimeric protein with near native pre-fusion conformation prepared using the primary sequence of an HIV-1 clade C env isolated from the broadly cross neutralizing plasma of an elite neutralizer. This novel SOSIP Env trimer demonstrated comparable antigenic, structural and immunogenic properties that favoured several ongoing subunit vaccine design efforts. The novel clade C SOSIP induced polyclonal neutralizing antibody response developed in rabbits not only differed in its epitope specificity compared to that elicited in natural infection in presence of pool of viral quasispecies but also showed how they differ in their ability to influence Env structure and conformation. A better understanding of how vaccine-induced polyclonal neutralizing antibody responses compares to responses that developed in natural infection will improve our knowledge in designing better vaccine design strategies.

immunology↗

bioRxiv2020

Design of a highly thermotolerant, immunogenic SARS-CoV-2 spike fragment

Virtually all SARS-CoV-2 vaccines currently in clinical testing are stored in a refrigerated or frozen state prior to use. This is a major impediment to deployment in resource-poor settings. Several use viral vectors or mRNA. In contrast to protein subunit vaccines, there is limited manufacturing expertise for these novel, nucleic acid based modalities, especially in the developing world. Neutralizing antibodies, the clearest known correlate of protection against SARS-CoV-2, are primarily directed against the Receptor Binding Domain (RBD) of the viral spike protein. We describe a monomeric, glycan engineered RBD protein fragment that is expressed at a purified yield of 214mg/L in unoptimized, mammalian cell culture and in contrast to a stabilized spike ectodomain, is tolerant of exposure to temperatures as high as 100{degrees}C when lyophilized, upto 70{degrees}C in solution and stable for over four weeks at 37{degrees}C. In prime:boost guinea pig immunizations, when formulated with the MF59 like adjuvant AddaVax, the RBD derivative elicited neutralizing antibodies with an endpoint geometric mean titer of ~415 against replicative virus, comparing favourably with several vaccine formulations currently in the clinic. These features of high yield, extreme thermotolerance and satisfactory immunogenicity suggest that such RBD subunit vaccine formulations hold great promise to combat COVID-19.

biophysics↗

bioRxiv2020

Non-parametric modelling of temporal and spatial counts data from RNA-seq experiments

AO_SCPLOWBSTRACTC_SCPLOWO_ST_ABSMotivationC_ST_ABSThe negative binomial distribution has been shown to be a good model for counts data from both bulk and single-cell RNA-sequencing (RNA-seq). Gaussian process (GP) regression provides a useful non-parametric approach for modeling temporal or spatial changes in gene expression. However, currently available GP regression methods that implement negative binomial likelihood models do not scale to the increasingly large datasets being produced by single-cell and spatial transcriptomics. ResultsThe GPcounts package implements GP regression methods for modelling counts data using a negative binomial likelihood function. Computational efficiency is achieved through the use of variational Bayesian inference. The GP function models changes in the mean of the negative binomial likelihood through a logarithmic link function and the dispersion parameter is fitted by maximum likelihood. We validate the method on simulated time course data, showing that it is better able to identify changes in over-dispersed counts data than methods based on Gaussian or Poisson likelihoods. To demonstrate temporal inference, we apply GPcounts to single-cell RNA-seq datasets after pseudotime and branching inference. To demonstrate spatial inference, we apply GPcounts to data from the mouse olfactory bulb to identify spatially variable genes and compare to two published GP methods. We also provide the option of modelling additional dropout using a zero-inflated negative binomial. Our results show that GPcounts can be used to model temporal and spatial counts data in cases where simpler Gaussian and Poisson likelihoods are unrealistic. AvailabilityGPcounts is implemented using the GPflow library in Python and is available at https://github.com/ManchesterBioinference/GPcounts along with the data, code and notebooks required to reproduce the results presented here. Contactnuha.bintayyash@manchester.ac.uk or magnus.rattray@manchester.ac.uk

bioinformatics↗

bioRxiv2020

Genetic analysis of amyotrophic lateral sclerosis identifies contributing pathways and cell types.

Despite the considerable progress in unraveling the genetic causes of amyotrophic lateral sclerosis (ALS), we do not fully understand the molecular mechanisms underlying the disease. We analyzed genome-wide data involving 78,500 individuals using a polygenic risk score approach to identify the biological pathways and cell types involved in ALS. This data-driven approach identified multiple aspects of the biology underlying the disease that resolved into broader themes, namely neuron projection morphogenesis, membrane trafficking, and signal transduction mediated by ribonucleotides. We also found that genomic risk in ALS maps consistently to GABAergic cortical interneurons and oligodendrocytes, as confirmed in human single-nucleus RNA-seq data. Using two-sample Mendelian randomization, we nominated five differentially expressed genes (ATG16L2, ACSL5, MAP1LC3A, PLXNB2, and SCFD1) within the significant pathways as relevant to ALS. We conclude that the disparate genetic etiologies of this fatal neurological disease converge on a smaller number of final common pathways and cell types.

genetics↗

bioRxiv2020

Aspirin inhibition of prostaglandin synthesis impairs egg development across mosquito taxa

Several endocrine signals are known to mediate mosquito egg development including insulin-like peptide, 20-hydroxyecdysone, and juvenile hormone. The objective of this study was to determine the effects of prostaglandin E2 (PGE2) as an additional mediator of oogenesis in the mosquitoes, Aedes albopictus and Anopheles gambiae. The injection of aspirin (an inhibitor of cyclooxygenase) shortly after blood-feeding significantly inhibited egg development at choriogenesis in a dose-dependent manner in Ae. albopictus. Moreover, oral administration of aspirin to An. albopictus and An. gambiae also inhibited egg production. The aspirin treatment suppressed expression of the genes (Yellow-g and Yellow-g2) associated with exochorion darkening and led to the production of a malformed egg shell in Ae. albopictus. These inhibitory effects of aspirin on egg development were rescued by the addition of PGE2, confirming the specificity of aspirin in inhibiting prostaglandin production. To validate these results, we identified a putative PGE2 receptor (Aa-PGE2R) in Ae. albopictus. Aa-PGE2R expression was highly inducible in adult ovary after blood-feeding. RNA interference of Aa-PGE2R expression resulted in the significant suppression of choriogenesis similar to aspirin treatment, where the addition of PGE2 to Aa-PGE2R-silenced females failed to rescue egg production. Together, these results suggest that PG synthesis and signaling are required for egg development across diverse mosquito taxa. Author SummaryProgstaglandins (PGs) play crucial roles in mediating various physiological processes in insects. Aspirin (ASP) inhibits PG biosynthesis and has been used as an anti-inflammatory drug. ASP injection or feeding to mosquitoes of Aedes albopictus or Anopheles gambiae significantly inhibits egg production at chorion formation. This led to significant reduction in fecundity and egg hatchability. PG signal is interrupted by RNA interference (RNAi) of PGE2 receptor. The RNAi treatment also gave a similar damage to females in egg production as seen in ASP treatment. Thus, PG signal is required for egg production of these mosquitoes. Data Availability StatementAll relevant data are within the manuscript and its Supporting Information file.

developmental biology↗

bioRxiv2020

Prostaglandin catabolism in Spodoptera exigua, a lepidopteran insect

Several prostaglandins (PGs) and PG-synthesizing enzymes have been identified from insects. PGs can mediate cellular and humoral immune responses. However, uncontrolled and prolonged immune responses might have adverse effects on survival. PG catabolism in insects has not been reported. Here, using a transcriptomic analysis, we predicted two PG-degrading enzymes, PG dehydrogenase (SePGDH) and PG reductase (SePGR), in Spodoptera exigua, a lepidopteran insect. SePGDH and SePGR expression levels were upregulated after immune challenge. However, their expression peaks occurred after those of PG biosynthesis genes such as PGE2 synthase or PGD2 synthase. Indeed, SePGDH and SePGR expression levels were upregulated after injection with PGE2 or PGD2. In contrast, such upregulated expression was not detected after injection with leukotriene B4, an eicosanoid inflammatory mediator. RNA interference (RNAi) using double-stranded RNAs specific to SePGDH or SePGR suppressed their expression levels. The RNAi treatment resulted in an excessive and fatal melanization of larvae even after a non-pathogenic bacterial infection. Phenoloxidase (PO) activity mediating the melanization in larval plasma was induced by bacterial challenge or PGE2 injection. Although the induced PO activity decreased after 8 h in control, larvae treated with dsRNAs specific to PG-degrading enzyme genes kept the high PO activities for a longer period compared to control larvae. These results suggest that SePGDH and SePGR are responsible for PG degradation at a late phase of immune responses.

immunology↗

bioRxiv2020

Genome sequencing analysis identifies new loci associated with Lewy body dementia and provides insights into the complex genetic architecture

The genetic basis of Lewy body dementia (LBD) is not well understood. Here, we performed whole-genome sequencing in large cohorts of LBD cases and neurologically healthy controls to study the genetic architecture of this understudied form of dementia and to generate a resource for the scientific community. Genome-wide association analysis identified five independent risk loci, whereas genome-wide gene-aggregation tests implicated mutations in the gene GBA. Genetic risk scores demonstrate that LBD shares risk profiles and pathways with Alzheimer’s and Parkinson’s disease, providing a deeper molecular understanding of the complex genetic architecture of this age-related neurodegenerative condition.Competing Interest StatementThomas G. Beach is a consultant for Prothena, Vivid Genomics and Avid Radiopharmaceuticals. He is a scientific advisory board member for Vivid Genomics. John A. Hardy, Huw R. Morris, Stuart Pickering-Brown, Andrew B. Singleton, and Bryan J. Traynor hold US, EU and Canadian patents on the clinical testing and therapeutic intervention for the hexanucleotide repeat expansion of C9orf72. Michael A. Nalls is supported by a consulting contract between Data Tecnica International and the National Institute on Aging, NIH, Bethesda, MD, USA; as a possible conflict of interest Dr. Nalls also consults for Neuron23 Inc., Lysosomal Therapeutics Inc., Illumina Inc., the Michael J. Fox Foundation and Vivid Genomics among others. Jose A. Palma is an editorial board member of Movement Disorders, Parkinsonism & Related Disorders, BMC Neurology, and Clinical Autonomic Research. Bradley F. Boeve, James Leverenz, and Sonja W. Scholz serve on the Scientific Advisory Council of the Lewy Body Dementia Association. Sonja W. Scholz is an editorial board member for the Journal of Parkinson's Disease. Bryan J. Traynor is an editorial board member for JAMA Neurology; Journal of Neurology, Neurosurgery, and Psychiatry; Brain; and Neurobiology of Aging. Zbigniew K. Wszolek serves as a principal investigator or co-principal investigator on Abbvie, Inc. (M15-562 and M15-563), Biogen, Inc. (228PD201) grant, and Biohaven Pharmaceuticals, Inc. (BHV4157-206 and BHV3241-301). Zbigniew K. Wszolek serves as the principal investigator of the Mayo Clinic American Parkinson Disease Association (APDA) Information and Referral Center, and as co-principal investigator of the Mayo Clinic APDA Center for Advanced Research. All other authors report no competing interests.View Full Text

genomics↗

bioRxiv2020

The extent and impact of variation in ADME genes in sub-Saharan African populations

Investigating variation in genes involved in the absorption, distribution, metabolism, and excretion (ADME) of drugs are key to characterising pharmacogenomic (PGx) relationships. ADME gene variation is relatively well characterised in European and Asian populations, but African populations are under-studied - which has implications for safe and effective drug use in Africa. The genetic diversity of ADME genes across sub-Saharan African populations is large. The Southern African population cluster is most distinct from that of far West Africa. PGx strategies based on European variants will be of limited use in African populations. Although established variants are important, PGx must take into account the full range of African variation. This work urges further characterisation of variants in African populations including in vitro and in silico studies, and to consider the unique African ADME landscape when developing precision medicine guidelines and tools for African populations. Author summaryThe ADME genes are a group of genes that play a key role in absorption, distribution, metabolism and excretion of drugs. Variations in these genes can have a significant impact on drug safety and efficacy. Africa has a high level of genetic variation and is under-studied in drug development, which makes study of variations in these genes in African populations very important. Using a new data set of 458 high-coverage genomes from across Africa, we characterise the extent and impact of variation in the ADME genes, looking at both single nucleotide and copy number variations. We identified 343,368 variants, including 40,692 novel variants, and 930 coding variants which are predicted to have high impact on function. Our discovery curves indicate that there will be considerable value in sequencing more African genomes. Moreover, relatively few of these novel variants are captured on common genotyping arrays. We show that there is considerable diversity within Africa in some important genes, and this will have significant consequences for the emerging field of precision medicine in Africa.

genetics↗

bioRxiv2020

Epitope-Based Peptide Vaccine Against Severe Acute Respiratory Syndrome-Coronavirus-2 Nucleocapsid Protein: An in silico Approach

With an increasing fatality rate, severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) has emerged as a promising threat to human health worldwide. SARS-CoV-2 is a member of the Coronaviridae family, which is transmitted from animal to human and because of being contagious, further it transmitted human to human. Recently, the World Health Organization (WHO) has announced the infectious disease caused by SARS-CoV-2, which is known as coronavirus disease-2019 (COVID-2019) as a global pandemic. But, no specific medications are available for the treatment of COVID-19 so far. As a corollary, there is a need for a potential vaccine to impede the progression of the disease. Lately, it has been documented that the nucleocapsid (N) protein of SARS-CoV-2 is responsible for viral replication as well as interferes with host immune responses. We have comparatively analyzed the sequences of N protein of SARS-CoV-2 for the identification of core attributes and analyzed the ancestry through phylogenetic analysis. Subsequently, we have predicted the most immunogenic epitope for T-cell as well as B-cell. Importantly, our investigation mainly focused on major histocompatibility complex (MHC) class I potential peptides and NTASWFTAL interacted with most human leukocyte antigen (HLA) that are encoded by MHC class I molecules. Further, molecular docking analysis unveiled that NTASWFTAL possessed a greater affinity towards HLA and also available in a greater range of the population. Our study provides a consolidated base for vaccine design and we hope that this computational analysis will pave the way for designing novel vaccine candidates.

bioinformatics↗

bioRxiv2020

Analysis of Ten Microsecond simulation data of SARS-CoV-2 dimeric main protease

The dimeric main protease of SARS-CoV-2, has become a crucial target for inhibiting/modulating its catalytic activity. However, understanding of its conformational change, and atomistic flexibility, is very much lucrative for designing/developing small molecules. Fortunately, huge data has been revealed by a research group, performed about ten-microsecond molecular dynamics to paving the way for understanding the structural complexity of protease. Herein, we have done the basic structural analysis, advanced flexibility and conformational analysis like PCA, for revealing out the regions and residues, which are mostly flexible and likely to be responsible for different conformation of protease protein.

bioinformatics↗

bioRxiv2020

The development of a novel diagnostic PCR for Madurella mycetomatis using a comparative genome approach

Eumycetoma is a neglected tropical disease characterized by large tumorous lesions. It is most commonly caused by the fungus Madurella mycetomatis which accounts for more than 70% of cases in central Africa. Currently, identification of the causative agent can only be reliably performed by a species-specific PCR. However, we recently demonstrated that our M. mycetomatis specific PCR can cross-react with Madurella pseudomycetomatis. We therefore used a comparative genome approach to develop a new M. mycetomatis specific PCR for species identification. For this we compared the published M. mycetomatis genome to genomes of other organisms in BLASTCLUST to identify unique M. mycetomatis predicted protein coding sequences. Based on 16 of these unique sequences, PCR primers were developed. The specificity of these primers was further evaluated in other eumycetoma causing agents including the Madurella sibling species. Out of the 16 tested sequences, only one was unique for M. mycetomatis and this should be used as a novel diagnostic marker for M. mycetomatis.

microbiology↗

bioRxiv2020

Reagentless Biomolecular Analysis Using a Nanoscale Molecular Pendulum

The ability to sense biological inputs using self-contained devices unreliant on external reagents or reporters would open countless opportunities to collect information about our health and environment. Currently, a very limited set of molecular inputs can be detected using this type of sensor format. The development of versatile reagentless sensors that could track molecular analytes in biological fluids remains an unmet need. Here, we describe a new universal sensing mechanism that is compatible with the analysis of proteins that are important physiological markers of stress, allergy, cardiovascular health, inflammation and cancer. The sensing mechanism we developed is based on the measurement of field-induced directional diffusion of a nanoscale molecular pendulum tethered to an electrode surface and the sensitivity of electron-transfer reaction kinetics to molecular size. Using time-resolved electrochemical measurements of diffusional motion, the presence of an analyte bound to a sensor complex can be continuously tracked in real time. We show that this sensing approach is compatible with making measurements in blood, saliva, urine, tears and sweat and that the sensors can collect data in situ in living animals. The sensor platform described enables a broad range of applications in personalized health monitoring.

bioengineering↗

bioRxiv2020

A convNet based multi-label microRNA subcellular location predictor, by incorporating k-mer positional encoding

MicroRNAs are special RNA sequences containing 22 nucleotides and are capable of regulating almost 60% of highly complex mammalian transcriptome. Presently, there exists very limited approaches capable of visualizing miRNA locations inside cell to reveal the hidden pathways, and mechanisms behind miRNA functionality, transport, and biogenesis. State-of-the-art miRNA sub-cellular location prediction MIRLocatar approach makes use of sequence to sequence model along with pre-train k-mer embeddings. Existing pre-train k-mer embedding generation methodologies focus on the extraction of semantics of k-mers. In RNA sequences, rather than semantics, positional information of nucleotides is more important because distinct positions of four basic nucleotides actually define the functionality of RNA molecules. Considering the dynamicity and importance of nucleotides positions, instead of learning representation on the basis of k-mers semantics, we propose a novel kmerRP2vec feature representation approach that fuses positional information of k-mers to randomly initialized neural k-mer embeddings. Effectiveness of proposed feature representation approach is evaluated with two deep learning based convolutional neural network CNN and recurrent neural network RNN methodologies using 8 evaluation measures. Experimental results on a public benchmark miRNAsubloc dataset prove that proposed kmerRP2vec approach along with a simple CNN model outperforms state-of-the-art MirLocator approach with a significant margin of 18% and 19% in terms of precision and recall.

genomics↗

bioRxiv2020

Bacteriophage SP01 Gene Product 56 (gp56) Inhibits Bacillus subtilis Cell Division by Interacting with DivIC/FtsL to Prevent Pbp2B/FtsW Recruitment

Previous work identified gp56, encoded by the lytic bacteriophage SP01, as responsible for inhibition of Bacillus subtilis cell division during its infection. Assembly of the essential tubulin-like protein FtsZ into a ring-shaped structure at the nascent site of cytokinesis determines the timing and position of division in most bacteria. This FtsZ ring serves as a scaffold for recruitment of other proteins into a mature division-competent structure permitting membrane constriction and septal cell wall synthesis. Here we show that expression of the predicted 9.3-kDa gene product 56 (gp56) of SP01 inhibits latter stages of B. subtilis cell division without altering FtsZ ring assembly. GFP-tagged gp56 localizes to the membrane at the site of division. While its localization permits recruitment of early division proteins, gp56 interferes with the recruitment of late division proteins, including Pbp2b and FtsW. Imaging of cells with specific division components deleted or depleted and two-hybrid analysis suggest that gp56 localization and activity depends on its interaction with mid-recruited proteins DivIC and/or FtsL. Together these data support a model where gp56 interacts with a central part of the division machinery to disrupt late recruitment of the division proteins involved in septal cell wall synthesis. IMPORTANCEResearch over the past decades has uncovered bacteriophage-encoded factors that interfere with host cell shape or cytokinesis during viral infection. Phage factors that cause cell filamentation that have been investigated to date all act by targeting FtsZ, the conserved prokaryotic tubulin homolog that composes the cytokinetic ring in most bacteria and some groups of archaea. However, the mechanism of several identified phage factors that inhibit cytokinesis remain unexplored, including gp56 of bacteriophage SP01 of Bacillus subtilis. Here, we show that unlike related published examples of phage inhibition of cyotkinesis, gp56 blocks B. subtilis cell division without targeting FtsZ. Rather, it utilizes the assembled FtsZ cytokinetic ring to localize to the division machinery and block recruitment of proteins needed for the septal cell wall synthesis.

microbiology↗

bioRxiv2020

Longitudinal whole-exome sequencing of cell-free DNA unravels the metastatic evolutionary dynamics of BRCA2 mutated breast cancer

Little is known about the metastatic evolutionary dynamics of BRCA2-mutated cancers. Here, we applied whole-exome sequencing (WES) of primary tumor (PT), local relapse (LR) and eight serial plasma cfDNA samples collected from disease progression to depict the 12 years evolutionary trajectory of a metastatic BRCA2-mutated breast cancer. While longitudinal WES-cfDNA recapitulated clonal and subclonal mutations and copy number profiles detected in LR, emergence of plasma-exclusive mutations in TSC2 and HDAC9 cancer-related genes and loss of HLA loci as an immune escape mechanism were also detected. Lastly, mutation signature 3, associated with homologous recombination deficiency and response to platinum-based therapy raised profoundly from 19% in PT to 60% in late stage disease. In conclusion, we show for the first time that longitudinal WES-cfDNA enables the evolutionary trajectory of advanced cancer to be uncovered and that increment of MS3 and loss of HLA are key players in this BRCA2-mutated breast metastasis.

cancer biology↗

bioRxiv2019

iPromoter-BnCNN: a Novel Branched CNN Based Predictor for Identifying and Classifying Sigma Promoters

MotivationPromoter is a short region of DNA which is responsible for initiating transcription of specific genes. Development of computational tools for automatic identification of promoters is in high demand. According to the difference of functions, promoters can be of different types. Promoters may have both intra and inter class variation and similarity in terms of consensus sequences. Accurate classification of various types of sigma promoters still remains a challenge. ResultsWe present iPromoter-BnCNN for identification and accurate classification of six types of promoters -{sigma} 24,{sigma} 28,{sigma} 32,{sigma} 38,{sigma} 54,{sigma} 70. It is a CNN based classifier which combines local features related to monomer nucleotide sequence, trimer nucleotide sequence, dimer structural properties and trimer structural properties through the use of parallel branching. We conducted experiments on a benchmark dataset and compared with six state-of-the-art tools to show our supremacy on 5-fold cross-validation. Moreover, we tested our classifier on an independent test dataset. AvailabilityOur proposed tool iPromoter-BnCNN web server is freely available at http://103.109.52.8/iPromoter-BnCNN. The runnable source code can be found here. Contactrafeed@cse.uiu.ac.bd Supplementary informationSupplementary data (benchmark dataset, independent test dataset, model files, structural property information, attention mechanism details and web server usage) are available at Bioinformatics. online.

genomics↗