Biology subjects

Kumar, S.

Publications and source records attributed to Kumar, S..

At least 631 records · Page 35Linked to original sources

bioRxiv2019

Power and pitfalls of computational methods for inferring clone phylogenies and mutation orders from bulk sequencing data

BackgroundTumors harbor extensive genetic heterogeneity in the form of distinct clone genotypes that arise over time and across different tissues and regions of a cancer patient. Many computational methods produce clone phylogenies from population bulk sequencing data collected from multiple tumor samples. These clone phylogenies are used to infer mutation order and clone origin times during tumor progression, rendering the selection of the appropriate clonal deconvolution method quite critical. Surprisingly, absolute and relative accuracies of these methods in correctly inferring clone phylogenies have not been consistently assessed.\n\nMethodsWe evaluated the performance of seven computational methods in producing clone phylogenies for simulated datasets in which clones were sampled from multiple sectors of a primary tumor (multi-region) or primary and metastatic tumors in a patient (multi-site). We assessed the accuracy of tested methods metrics in determining the order of mutations and the branching pattern within the reconstructed clone phylogenies.\n\nResultsThe accuracy of the reconstructed mutation order varied extensively among methods (9% - 44% error). Methods also varied significantly in reconstructing the topologies of clone phylogenies, as 24% - 58% of the inferred clone groupings were incorrect. All the tested methods showed limited ability to identify ancestral clone sequences present in tumor samples correctly. The occurrence of multiple seeding events among tumor sites during metastatic tumor evolution hindered deconvolution of clones for all tested methods.\n\nConclusionsOverall, CloneFinder, MACHINA, and LICHeE showed the highest overall accuracy, but none of the methods performed well for all simulated datasets and conditions.

cancer biology↗

bioRxiv2019

Reliable confidence intervals for RelTime estimates of evolutionary divergence times

Confidence intervals (CIs) depict the statistical uncertainty surrounding evolutionary divergence time estimates. They capture variance contributed by the finite number of sequences and sites used in the alignment, deviations of evolutionary rates from a strict molecular clock in a phylogeny, and uncertainty associated with clock calibrations. Reliable tests of biological hypotheses demand reliable CIs. However, current non-Bayesian methods may produce unreliable CIs because they do not incorporate rate variation among lineages and interactions among clock calibrations properly. Here, we present a new analytical method to calculate CIs of divergence times estimated using the RelTime method, along with an approach to utilize multiple calibration uncertainty densities in these analyses. Empirical data analyses showed that the new methods produce CIs that overlap with Bayesian highest posterior density (HPD) intervals. In the analysis of computer-simulated data, we found that RelTime CIs show excellent average coverage probabilities, i.e., the true time is contained within the CIs with a 95% probability. These developments will encourage broader use of computationally-efficient RelTime approach in molecular dating analyses and biological hypothesis testing.

evolutionary biology↗

bioRxiv2019

Biophysical principles of choanoflagellate self-organization

Inspired by the patterns of multicellularity in choanoflagellates, the closest living relatives of animals, we quantify the biophysical processes underlying the morphogenesis of rosette colonies in the choanoflagellate Salpingoeca rosetta. We find that rosettes reproducibly transition from an early stage of 2D growth to a later stage of 3D growth, despite the underlying stochasticity of the cell lineages. We postulate that the extracellular matrix (ECM) exerts a physical constraint on the packing of proliferating cells, thereby sculpting rosette morphogenesis. Our perturbative experiments coupled with biophysical simulations demonstrates the fundamental importance of a basally-secreted ECM for rosette morphogenesis. In addition, this yields a morphospace for the shapes of these multicellular colonies, consistent with observations of a range of choanoflagellates. Overall, our biophysical perspective on rosette development complements previous genetic perspectives and thus helps illuminate the interplay between cell biology and physics in regulating morphogenesis.\n\nSignificance statementComparisons among animals and their closest living relatives, the choanoflagellates, have begun to shed light on the origin of animal multicellularity and development. Here we complement previous genetic perspectives on this process by focusing on the biophysical principles underlying colony morphology and morphogenesis. Our study reveals the crucial role of the extracellular matrix in shaping the colonies and leads to a phase diagram that delineates the range of morphologies as a function of the biophysical mechanisms at play.

biophysics↗

bioRxiv2019

Relating anthropometric indicators to brain structure in 2-month-old Bangladeshi infants growing up in poverty: a pilot study

Anthropometric indicators, including stunting, underweight, and wasting, have previously been associated with poor neurocognitive outcomes. This link may exist because malnutrition and infection, which are known to affect height and weight, also impact brain structure according to animal models. However, a relationship between anthropometric indicators and brain structural measures has not been tested yet, perhaps because stunting, underweight, and wasting are uncommon in higher-resource settings. Further, with diminished anthropomorphic growth prevalent in low-resource settings, where biological and psychosocial hazards are most severe, one might expect additional links between measures of poverty, anthropometry, and brain structure. To begin to examine these relationships, we conducted an MRI study in 2-3-month-old infants growing up in the extremely impoverished urban setting of Dhaka, Bangladesh. The sample size was relatively small because the challenges of investigating infant brain structure in a low-resource setting needed to be realized and resolved before introducing a larger cohort. Initially, fifty-four infants underwent T1 sequences using 3T MRI, and structural images were segmented into gray and white matter maps, which were carefully evaluated for accurate tissue labeling by a pediatric neuroradiologist. Gray and white matter volumes from 29 infants (79 {+/-} 10 days-of-age; F/M = 12/17), whose segmentations were of relatively high quality, were submitted to semi-partial correlation analyses with stunting, underweight, and wasting, which were measured using height-for-age (HAZ), weight-for-age (WAZ), and weight-for-height (WHZ) scores. Positive semi-partial correlations (after adjusting for chronological age and sex and correcting for multiple comparisons) were observed between white matter volume and HAZ and WAZ; however, WHZ was not correlated with any measure of brain volume. In examining the role of poverty, no associations were observed between income-to-needs or maternal education and brain volumetric measures, suggesting that risk factors previously linked with poverty were not associated with total brain tissue volume pre- or peri-natally in this sample. Overall, these results provide the first link between diminished anthropomorphic growth and white matter volume in infancy. Challenges of conducting a developmental neuroimaging study in a low-resource country are described.

neuroscience↗

bioRxiv2019

Meta-taxonomic Analysis of Prokaryotic and Eukaryotic Gut Flora in Stool Samples from Visceral Leishmaniasis Cases and Endemic Controls in Bihar State India

Visceral leishmaniasis (VL) caused by Leishmania donovani remains of public health concern in rural India. Those at risk of VL are also at risk of other neglected tropical diseases (NTDs) including soil transmitted helminths. Intestinal helminths are potent regulators of host immune responses sometimes mediated through cross-talk with gut microbiota. We evaluate a meta-taxonomic approach to determine the composition of prokaryotic and eukaryotic gut microflora using amplicon-based sequencing of 16S ribosomal RNA (16S rRNA) and 18S rRNA gene regions. The most abundant bacterial taxa identified in faecal samples from Bihar State India were Prevotella (37.1%), Faecalibacterium (11.3%), Escherichia-Shigella (9.1%), Alloprevotella (4.5%), Bacteroides (4.1%), Ruminococcaceae UCG-002 (1.6%), and Bifidobacterium (1.5%). Eukaryotic taxa identified (excluding plant genera) included Blastocystis (57.9%; Order: Stramenopiles), Dientamoeba (12.1%; Family: Tritrichomonadea), Pentatrichomonas (10.1%; Family: Trichomonodea), Entamoeba (3.5%; Family: Entamoebida), Ascaridida (0.8%; Family: Chromodorea; concordant with Ascaris by microscopy), Rhabditida (0.8%; Family: Chromodorea; concordant with Strongyloides), and Cyclophyllidea (0.2%; Order: Eucestoda; concordant with Hymenolepis). Overall alpha (Shannons, Faiths and Pielous indices) and beta (Bray-Curtis dissimilarity statistic; weighted UniFrac distances) diversity of taxa did not differ significantly by age, sex, geographic subdistrict, or VL case (N=23) versus endemic control (EC; N=23) status. However, taxon-specific associations occurred: (i) Ruminococcaceae UCG-014 and Gastranaerophilales_uncultured bacterium were enriched in EC compared to VL cases; (ii) Pentatrichomonas was more abundant in VL cases than in EC, whereas the reverse occurred for Entamoeba. Across the cohort, high Escherichia-Shigella was associated with reduced bacterial diversity, while high Blastocystis was associated with high bacterial diversity and low Escherichia-Shigella. Individuals with high Blastocystis had low Bacteroidaceae and high Clostridiales vadin BB60 whereas the reverse held true for low Blastocystis. This scoping study provides useful baseline data upon which to develop a broader analysis of pathogenic enteric microflora and their influence on gut microbial health and NTDs generally.\n\nAuthor SummaryVisceral leishmaniasis (VL), also known as kala-azar, is a potentially fatal disease caused by intracellular parasites of the Leishmania donovani complex. VL is a serious public health problem in rural India, causing high morbidity and mortality, as well as major costs to local and national health budgets. People at risk of VL are also at risk of other neglected tropical diseases (NTDs) including soil transmitted helminths (worms). Intestinal worms are potent regulators of host immune responses often mediated through cross-talk with gut bacteria. Here we have used a modern DNA sequencing approach to determine the composition of microbiota in stool samples from VL cases and endemic controls. This allows us to determine all bacteria, as well as all single-celled and multicellular organisms, that comprise the microorganisms in the gut in a single sequencing experiment from a single stool sample. In addition to providing valuable information concerning commensal and pathogenic gut micro-organisms prevalent in this region of India, we find some specific associations between single-celled gut pathogens and VL case status.

genomics↗

bioRxiv2019

Uncovering and characterizing splice variants associated with survival in lung cancer patients

Splice variants have been shown to play an important role in tumor initiation and progression and can serve as novel cancer biomarkers. However, the clinical importance of individual splice variants and the mechanisms by which they can perturb cellular functions are still poorly understood. To address these issues, we developed an efficient and robust computational method to: (1) identify splice variants that are associated with patient survival in a statistically significant manner; and (2) predict rewired protein-protein interactions that may result from altered patterns of expression of such variants. We applied our method to the lung adenocarcinoma dataset from TCGA and identified splice variants that are significantly associated with patient survival and can alter protein-protein interactions. Among these variants, several are implicated in DNA repair through homologous recombination. To computationally validate our findings, we characterized the mutational signatures in patients, grouped by low and high expression of a splice variant associated with patient survival and involved in DNA repair. The results of the mutational signature analysis are in agreement with the molecular mechanism suggested by our method. To the best of our knowledge, this is the first attempt to build a computational approach to systematically identify splice variants associated with patient survival that can also generate experimentally testable, mechanistic hypotheses. Code for identifying survival-significant splice variants using the Null Empirically Estimated P-value method can be found at https://github.com/thecodingdoc/neep. Code for construction of Multi-Granularity Graphs to discover potential rewired protein interactions can be found at https://github.com/scwest/SINBAD. Presentation slides are found at https://github.com/scwest/RECOMB-CBB_2019_NEEP.\n\nAuthor summaryIn spite of many recent breakthroughs, there is still a pressing need for better ways to diagnose and treat cancer in ways that are specific to the unique biology of the disease. Novel computational methods applied to large-scale datasets can help us reach this goal more effectively. In this work we shed light on a still poorly understood biological process that is often aberrant in cancer and that can lead to tumor formation, progression, and invasion. This mechanism is alternative splicing and is the ability of one gene to code for many different variants with distinct functions. We developed a fast and statistically robust approach to identify splice variants that are significantly associated with patient survival. Then, we computationally characterized the protein products of these splice variants by identifying potential losses and gains of protein interactions that could explain their biological role in cancer. We applied our method to a lung adenocarcinoma dataset and identified several splice variants associated with patient survival that lose biologically important interactions. We conducted case studies and computationally validated some of our results by finding mutation signatures that support the molecular mechanism suggested by our method.

bioinformatics↗

bioRxiv2019

A new method for inferring timetrees from temporally sampled molecular sequences

Pathogen timetrees are phylogenies scaled to time. They reveal the temporal history of a pathogen spread through the populations as captured in the evolutionary history of strains. These timetrees are inferred by using molecular sequences of pathogenic strains sampled at different times. That is, temporally sampled sequences enable the inference of sequence divergence times. Here, we present a new approach (RelTime with Dated Tips [RTDT]) to estimating pathogen timetrees based on the relative rate framework underlying the RelTime approach. RTDT does not require many of the priors demanded by Bayesian approaches, and it has light computing requirements. We found RTDT to be accurate on simulated datasets evolved under a variety of branch rates models. Interestingly, we found two non-Bayesian methods (RTDT and Least Squares Dating [LSD]) to perform similar to or better than the Bayesian approaches available in BEAST and MCMCTree programs. RTDT method was found to generally outperform all other methods for phylogenies in with autocorrelated evolutionary rates. In analyses of empirical datasets, RTDT produced dates that were similar to those from Bayesian analyses. Speed and accuracy of the new method, as compared to the alternatives, makes it appealing for analyzing growing datasets of pathogenic strains. Cross-platform MEGA X software, freely available from http://www.megasoftware.net, now contains the new method for use through a friendly graphical user interface and in high-throughput settings.\n\nAUTHOR SUMMARYPathogen timetrees trace the origins and evolutionary histories of strains in populations, hosts, and outbreaks. The tips of these molecular phylogenies often contain sampling time information because the sequences were generally obtained at different times during the disease outbreaks and propagation. We have developed a new method for inferring timetrees for phylogenies with tip dates, which improves on widely-used Bayesian methods (e.g., BEAST) in computational efficiency and does not require prior specification of population parameters, branch rate model, or clock model. We performed extensive computer simulation and found that RTDT performed better than the other methods for the estimation of divergence times at deep node in phylogenies where evolutionary rates were autocorrelated. The new method is available in the cross-platform MEGA software package that provides a graphical user interface, and allows use via a command line in scripting and high throughput analysis (www.megasoftware.net).

evolutionary biology↗

bioRxiv2019

Genetic mapping of fitness determinants across the malaria parasite Plasmodium falciparum life cycle

Malaria is transmitted through female Anopheline mosquitoes where gamete fusion and meiosis occurs, and humans where parasites proliferate asexually. We describe a powerful approach to identify the genetic determinants of parasite fitness across both invertebrate and vertebrate life-cycle stages in human malaria parasite Plasmodium falciparum using bulk segregant analysis (BSA). We combined experimental genetic crosses using humanized mice, with selective whole genome amplification and BSA at multiple developmental stages in both mosquito and vertebrate host to examine parasite competition and identify genomic regions under selection. We generated crosses between artemisinin resistant (ART-R, kelch13-C580Y) and ART-sensitive (ART-S, kelch13-WT) parasite clones recently isolated from Southeast Asian patients. We then quantified genome-wide changes in allele frequency in the parasite progeny population from infected midgut and salivary glands of Anopheles stephensi mosquitoes, infected livers, emerging merozoites and aliquots of in vitro cultured progeny parasites at intervals over 30 days. Three striking results emerge: we observed (i) a strong skew (>80%) towards alleles from the ART-R parent in the mosquito stage, that dropped to [~]50% in the blood stage as selfed ART-R parasites were selected against; (ii) highly repeatable skews in allele frequencies across the genome in blood stage parasites; (iii) particularly strong selection (selection coefficient (s) [≤] 0.18/asexual cycle) against alleles from the ART-R parent at loci on chromosome 12 containing MRP2 and chromosome 14 containing ARPS10. This approach robustly identifies selected loci and has strong potential for identifying parasite genes that interact with the mosquito vector or compensatory loci involved in drug resistance.

evolutionary biology↗

bioRxiv2019

Molecular dating for phylogenies containing a mix of populations and species

Concurrent molecular dating of population and species divergences is essential in many biological investigations, including phylogeography, phylodynamics, and species delimitation studies. Multiple sequence alignments used in these investigations frequently consist of both intra- and inter-species samples (mixed samples). As a result, the phylogenetic trees contain inter-species, inter-population, and within population divergences. To date these sequence divergences, Bayesian relaxed clock methods are often employed, but they assume the same tree prior for both inter- and intra-species branching processes and require specification of a clock model for branch rates (independent vs. autocorrelated rates models). We evaluated the impact of using the same tree prior on the Bayesian divergence time estimates by analyzing computer-simulated datasets. We also examined the effect of the assumption of independence of evolutionary rate variation among branches when the branch rates are autocorrelated. Bayesian approach with Skyline-coalescent tree priors generally produced excellent molecular dates, with some tree priors (e.g., Yule) performing the best when evolutionary rates were autocorrelated, and lineage sorting was incomplete. We compared the performance of the Bayesian approach with a non-Bayesian, the RelTime method, which does not require specification of a tree prior or selection of a clock model. We found that RelTime performed as well as the Bayesian approach, and when the clock model was mis-specified, RelTime performed slightly better. These results suggest that the computationally efficient RelTime approach is also suitable to analyze datasets containing both populations and species variation.

ecology↗

bioRxiv2019

Grass silica mineralizer (GSM1) protein precipitates silica in sorghum silica cells

O_LISilicon is absorbed by plant roots as silicic acid. The acid moves with the transpiration stream to the shoot, and mineralizes as silica. In grasses, leaf epidermal cells called silica cells deposit silica in most of their volume by unknown mechanism.\nC_LIO_LIUsing bioinformatics tools, we identified a previously uncharacterized protein in sorghum (Sorghum bicolor), which we named Siliplant1 (Slp1). Silica precipitation activity in vitro, expression profile, and activity in precipitating biosilica in vivo were characterized.\nC_LIO_LISlp1 is a basic protein with seven repeat units rich in proline, lysine, and glutamic acid. A short peptide, repeating five times in the protein precipitated silica in vitro at a biologically relevant silicic acid concentration. Raman and NMR spectroscopies showed that the peptide attached the silica through lysine amine groups, forming a mineral-peptide open structure. We found Slp1 expression in immature leaf and inflorescence tissues. In the immature leaf active silicification zone, Slp1 was localized to the cytoplasm or near cell boundaries of silica cells. It was packed in vesicles and secreted to the paramural space. Transient overexpression of Slp1 in sorghum resulted in ectopic silica deposition in all leaf epidermal cell types.\nC_LIO_LIOur results show that Slp1 precipitates silica in sorghum silica cells.\nC_LI

plant biology↗

bioRxiv2018

Physicochemical and microbiological profile of the potable water of Eastern Himalayan State Sikkim: An Indication of Severe Fecal Contamination and Immediate Health Risk

Increasing population, rapid urbanization and climate change have immensely affected the freshwater sources around the world. The continuous decline in the number of natural potable water sources raises serious concern about the overall health of the human population. Developing countries are the most affected in this regard due to lack of proper hygienic maintenance protocols. Sikkim an Eastern Himalayan state with mountains as predominant topological features, harbors several natural spring water (SW). These spring waters are the primary source of potable water for the population in the four districts of the state viz. East (E), West (W), South (S) and North (N). Several incidences of water-borne diseases and the relative lack of scientific evaluation reports on the water quality of the area have educed this study. Lack of any standard filtration and purification practice among the population is one of the prime factors for the outspread of different waterborne pathogen in the state. The people of the state mostly use boiling as a dominant method of water purification, while only a small percentage of people in the West district were found to use modern standard purification system (W = 30%). The rainy season was found to be the major contributor of different diseases (E = 86%; W=100%; S=100%; N=80%) and statistical analysis of the fecal coliforms of the different season also indicated a significant difference at p < 0.05. There was no statistical significance among the physicochemical parameter of the SW but surprisingly the water from the four districts was recorded with traces of highly toxic heavy metals like mercury/WHO limit (0.001-0.007mg/l/0.001) as well as lead/WHO limit (0.001-0.007mg/l/0.05) and selenium/WHO limit (0.526-0.644 mg/l/0.01) which was above the WHO permissible limit. Piper analysis showed that water was dominated by cation sodium ion (Na+) and bicarbonate (HCO3-) anion and the water can be categorized as Mg-HCO3- type. Pairwise Pearson correlation showed a significant correlation between Electrical conductivity and TDS (r = 0.998/1.00) as well as alkalinity and turbidity (0.993/1.00). The microbial confirmatory test showed severity in fecal contamination with high counts of Total Coliform (TC), Escherichia coli (EC) and Enterococcus (EN). Highest TC was recorded from W (37.26/ml) and lowest in N (22.13/ ml) in spring water. Highest contamination of Escherichia coli and Enterococcus was found in E (EC = 8.7/ml; EN = 2.08/ml) followed by S (EC = 8.4/ml and EN = 2.05/ml). It was found that community reservoir (CR) tank was more contaminated than SP, which indicates the negligence in maintenance and fecal contamination during transportation to the reservoir. Though household water was least contaminated compared to CR and SP, but it fails in WHO standard criteria for drinking water. These results indicate an immediate health risk of the resident of the state and which needs to be taken care of sooner as possible by protecting the important potable sources with required policies and regulations.

microbiology↗

bioRxiv2018

Leveraging protein dynamics to identify cancer mutational hotspots in 3D-structures

Large-scale exome sequencing of tumors has enabled the identification of cancer drivers using recurrence and clustering-based approaches. Some of these methods also employ three-dimensional protein structures to identify mutational hotspots in cancer-associated genes. In determining such mutational clusters in structures, existing approaches overlook protein dynamics, despite the essential role of dynamics in protein functionality. In this work, we present a framework to identify driver genes using a dynamics-based search of mutational hotspot communities. After partitioning 3D structures into distinct communities of residues using anisotropic network models, we map variants onto the partitioned structures. We then search for signals of positive selection among these residue communities to identify putative drivers. We applied our method using the TCGA pan-cancer atlas missense mutation catalog. Overall, our analyses predict one or more mutational hotspots within the resolved structures of 434 genes. Ontological and pathway enrichment analyses implicate genes with predicted hotspots to be enriched in biological processes associated with tumor progression. Additionally, a comparison between our approach and existing hotspot detection methods that use structural data suggests that the inclusion of dynamics significantly increases the sensitivity of driver detection.

bioinformatics↗

bioRxiv2018

The cortico-striatal circuit regulates sensorimotor gating via Disc1/Huntingtin-mediated Bdnf transport

Sensorimotor information processing that underlies normal cognitive and behavioral traits is dysregulated across a subset of neurological and psychiatric disorders. The cross-disease deficit in sensorimotor gating poses a unique opportunity to integrate hierarchical findings at molecular, cellular, through circuitry levels to obtain an in-depth mechanistic understanding of this process that contributes to brain physiology and pathophysiology beyond categorical segmentation of brain disorders. Based on circuitry recording with wild-type mice, we demonstrated that the cortico-striatal projection mediates sensorimotor gating responses during prepulse inhibition (PPI) task. We also found that these circuitry responses were disrupted in Disc1 locus-impairment (LI) mice, a model representing neuropsychiatric conditions. Thus, we hypothesized that Disc1-mediated molecular and cellular machinery along the cortico-striatal circuit may regulate sensorimotor gating. Anatomical and biochemical analyses of Disc1-LI mice revealed attenuated Bdnf transport along the cortico-striatal circuit. Pharmacologically augmenting Bdnf transport by chronic lithium administration, in part via Ser-421 phosphorylation of Huntingtin (Htt) and its integration into the motor machinery, restored the striatal Bdnf levels and PPI deficits in Disc1-LI mice, suggesting that the Bdnf transport attenuation mechanistically underlies the circuitry and behavioral deficits. These results also shed light on a novel mechanism and utility of lithium that is currently used as a major mood stabilizer in clinical settings. Collectively, the present study illustrates integrative biological mechanisms for sensorimotor gating, underscoring the cross-disease nature of this behavioral dimension and translational utility of the findings under the era of precision medicine in brain disorders.

neuroscience↗

bioRxiv2018

Silent crickets reveal the genomic footprint of recent adaptive trait loss

Secondary trait loss is widespread and has profound consequences, from generating diversity to driving adaptation. Sexual trait loss is particularly common1. Its genomic impact is challenging to reconstruct because most reversals occurred in the distant evolutionary past and must be inferred indirectly2, and questions remain about the extent of disruption caused by pleiotropy, altered gene expression and loss of homeostasis3. We tested the genomic signature of recent sexual signal loss in Hawaiian field crickets, Teleogryllus oceanicus. Song loss is controlled by a sex-linked Mendelian locus, flatwing, which feminises male wings by erasing sound-producing veins. This variant spread rapidly under pressure from an eavesdropping parasitoid fly. We sequenced, assembled and annotated the T. oceanicus genome, produced a high-density linkage map, and localised flatwing on the X chromosome. We characterised pleiotropic effects of flatwing, including changes in embryonic gene expression and alteration of another sexual signal, chemical pheromones. Song loss is associated with pleiotropy, hitchhiking and genome-wide regulatory disruption which feminises flatwing male pheromones. The footprint of recent adaptive trait loss illustrates R. A. Fishers influential prediction that variants with large mutational effect sizes can invade genomes during the earliest stages of adaptation to extreme pressures, despite having severely disruptive genomic consequences.

evolutionary biology↗

bioRxiv2018

Viral characteristics associated with sustenance of elite neutralizing activity in chronically HIV-1C infected monozygotic pediatric twins

Broad and potent neutralizing antibodies (bnAbs) with multiple epitope specificities evolve in HIV-1 infected children. Herein we studied two antiretroviral naive chronically HIV-1C in-fected monozygotic pediatric twins AIIMS_329 and AIIMS_330 with potent plasma bnAbs. Elite plasma neutralizing activity was observed since initial sampling at 78 months in AIIMS_330 and persisted throughout, while in AIIMS_329 it was seen at 90-months of age after which potency decreased overtime. We evaluated potential viral characteristics associated with the varied immune profile by generating single genome amplified pseudoviruses. The AIIMS_329 viruses generated from 90-month time point sampling were neutralization sensitive to second generation bnAbs and contemporaneous autologous plasma antibodies, while viruses from 112-months and 117-month timepoints were resistant to most bnAbs and autologous contemporaneous plasma. AIIMS_329 viruses developed resistance to plasma nAbs plausibly by N160-glycan loss, V1- and V4-loop lengthening. The viruses generated from AIIMS_330 at 90-month and 117-month timepoint showed varied susceptibility to bnAbs and autologous contemporaneous plasma antibodies while the viruses of 112-month timepoint, at which plasma nAb specificities mapped to the V2-glycan, V3-glycan and CD4bs, were resistant to autologous contemporaneous plasma antibodies as well as most bnAbs. We observed evolution of a viral pool in AIIMS_330 donor, comprising of plasma antibody neutralization sensitive or resistant diverse autologous viruses that in turn may have contributed to development and maintenance of elite neutralizing activity. The findings of this study provide information towards understanding factors involved in generation and maintenance of potent plasma nAbs.\n\nImportanceChronically HIV-1 infected children that develop elite neutralizing activity are suitable candidates to understand the mechanisms that lead to the co-evolution of virus and antibody response. Here, we evaluated the alterations in virus and antibody responses over time in chronically HIV-1C infected monozygotic pediatric twins, AIIMS_329 and AIIMS_330, who had acquired the infection by vertical transmission. AIIMS_330 retained the elite plasma neutralizing activity throughout, while in AIIMS_329, the potency decreased post 90 months of age. The corresponding viral pool from post 90-month samples in AIIMS_330 showed varied susceptibility, while that in AIIMS_329, developed resistance to bnAbs and autologous plasma antibodies. The findings of this study, conducted in twin children of same genetic make-up and infected at birth with a single source of HIV-1C, suggest that a viral pool with varied susceptibility to antibodies could have been one of the factors responsible for sustained elite neutralizing activity in AIIMS_330.

immunology↗

bioRxiv2018

On estimating evolutionary probabilities of population variants

BackgroundThe evolutionary probability (EP) of an allele in a DNA or protein sequence predicts evolutionarily permissible (ePerm; EP [≥] 0.05) and forbidden (eForb; EP < 0.05) variants. EP of an allele represents an independent evolutionary expectation of observing an allele in a population based solely on the long-term substitution patterns captured in a multiple sequence alignment. In the neutral theory, EP and population frequencies can be compared to identify neutral and non-neutral alleles. This approach has been used to discover candidate adaptive polymorphisms in humans, which are eForbs segregating with high frequencies. The original method to compute EP requires the evolutionary relationships and divergence times of species in the sequence alignment (a timetree), which are not known with certainty for most datasets. This requirement impedes a general use of the original EP formulation. Here, we present an approach in which the phylogeny and times are inferred from the sequence alignment itself prior to the EP calculation. We evaluate if the modified EP approach produces results that are similar to those from the original method. ResultsWe compared EP estimates from the original and the modified approaches by using more than 18,000 protein sequence alignments containing orthologous sequences from 46 vertebrate species. For the original EP calculations, we used species relationships from UCSC and divergence times from TimeTree web resource, and the resulting EP estimates were considered to be the ground truth. We found that the modified approaches produced reasonable EP estimates for HGMD disease missense variant and 1000 Genomes Project missense variant datasets. Our results showed that reliable estimates of EP can be obtained without a priori knowledge of the sequence phylogeny and divergence times. We also found that, in order to obtain robust EP estimates, it is important to assemble a dataset with many sequences, sampling from a diversity of species groups. ConclusionWe conclude that the modified EP approach will be generally applicable for alignments and enable the detection of potentially neutral, deleterious, and adaptive alleles in populations.

evolutionary biology↗

bioRxiv2018

Activation of Multiple Signalling Pathways by P152Lp53 Mutant Reveals New Gain-of-function Implicating Tumorigenesis

TP53 is the most frequently mutated tumor suppressor gene in context of all varieties of cancer, yet biochemical characterization of several reported mutations with probable biological significance have not been accomplished. We have identified a relatively rare proline to leucine mutation (P152L) in p53 in an Indian oral cancer patient sample at the fade end of its DNA binding domain (DBD). Although P152Lp53 DBD potentially binds to DNA, the full length protein is completely devoid of DNA binding ability at its cognate site. Interestingly, P152Lp53 can efficiently tetramerize. Significantly, this mutant when expressed in p53 null cell line, was found to induce cell mobility, proliferation, and invasion as compared to vector control. Also, enhanced tumorigenic potential was observed when cells expressing P152Lp53 were xenografted into nude mice, the mechanistic details of which were also investigated upon where several of the pathways were found to be upregulated such as Cell-Cell/Cell-ECM signalling, EGFR signalling, Rho-GTPase signalling. Taken together, this study establishes P152Lp53 as a new gain of function mutant.

cancer biology↗

bioRxiv2018

Genomic architecture and introgression shape a butterfly radiation

We here pioneer a low-cost assembly strategy for 20 Heliconiini genomes to characterize the evolutionary history of the rapidly radiating genus Heliconius. A bifurcating tree provides a poor fit to the data, and we therefore explore a reticulate phylogeny for Heliconius. We probe the genomic architecture of gene flow, and develop a new method to distinguish incomplete lineage sorting from introgression. We find that most loci with non-canonical histories arose through introgression, and are strongly underrepresented in regions of low recombination and high gene density. This is expected if introgressed alleles are more likely to be purged in such regions due to tighter linkage with incompatibility loci. Finally, we identify a hitherto unrecognized inversion, and show it is a convergent structural rearrangement that captures a known color pattern switch locus within the genus. Our multi-genome assembly approach enables an improved understanding of adaptive radiation.

evolutionary biology↗