Biology subjects

Singh, P.

Publications and source records attributed to Singh, P..

At least 181 records · Page 10Linked to original sources

bioRxiv2021

Dendrite regeneration in C. elegans is controlled by the RAC GTPase CED-10 and the RhoGEF TIAM-1

Neurons are vulnerable to physical insults which compromise the integrity of both dendrites and axons. Although several molecular pathways of axon regeneration are identified, our knowledge of dendrite regeneration is limited. To understand the mechanisms of dendrite regeneration, we used PVD neurons in C. elegans having stereotyped branched dendrites. Using femtosecond laser, we severed the primary dendrites and axon of this neuron. After severing the primary dendrites near the cell body, we observed sprouting of new branches from the proximal site within 6 hours, which regrew further with timein an unstereotyped manner.This was accompanied by reconnection between the proximal and distal dendrites as well as the fusion among the higher-order branches as reported before. We quantified the regeneration pattern in threeaspects -territory length, number of branchesand fusion phenomena.Axonal injury causes a retraction of the severed end followed by a Dual leucine zipper kinase-1 (DLK-1) dependent regrowth from the severed end.We tested the roles of the major axon regenerationsignaling hubs such as DLK-1-RPM-1, cAMP elevation, let-7 miRNA, AKT-1, Phosphatidyl serine exposure/PS in dendrite regeneration. We found that neither regrowth nor fusionis affected by the axon injury pathway molecules. Surprisingly, we found that the RAC GTPase CED-10and its upstream GEF TIAM-1 play a cell-autonomous role in dendrite regeneration. Additionally, function of CED-10 in epidermal cell is critical for post-dendrotomy fusion phenomena. This work describes a novel regulatory mechanism of dendrite regeneration andprovides a framework for understanding the cellular mechanism of dendrite regeneration using PVD neuron as a model system.

neuroscience↗

bioRxiv2021

Genomic sequencing of Lowe syndrome trios reveal a mechanism for the heterogeneity of neurodevelopmental phenotypes

Lowe syndrome is an X-linked recessive monogenic disorder resulting from mutations in the OCRL gene that encodes a phosphatidylinositol 4,5 bisphosphate 5-phosphatase. The disease affects three organs-the kidney, brain and eye and clinically manifests as proximal renal tubule dysfunction, neurodevelopmental delay and congenital cataract. Although Lowe syndrome is a monogenic disorder, there is considerable heterogeneity in clinical presentation; some individuals show primarily renal symptoms with minimal neurodevelopmental impact whereas others show neurodevelopmental defect with minimal renal symptoms. However, the molecular and cellular mechanisms underlying this clinical heterogeneity remain unknown. Here we analyze a Lowe syndrome family in whom affected members show clinical heterogeneity with respect to the neurodevelopmental phenotype despite carrying an identical mutation in the OCRL gene. Genome sequencing and variant analysis in this family identified a large number of damaging variants in each patient. Using novel analytical pipelines and segregation analysis we prioritize variants uniquely present in the patient with the severe neurodevelopmental phenotype compared to those with milder clinical features. The identity of genes carrying such variants underscore the role of additional gene products enriched in the brain or highly expressed during brain development that may be determinants of the neurodevelopmental phenotype in Lowe syndrome. We also identify a heterozygous variant in CEP290, previously implicated in ciliopathies that underscores the potential role of OCRL in regulating ciliary function that may impact brain development. More generally, our findings demonstrate analytic approaches to identify high-confidence genetic variants that could underpin the phenotypic heterogeneity observed in monogenic disorders.

genomics↗

bioRxiv2021

Aggregation state of Mycobacterium tuberculosis impacts host immunity and augments pulmonary disease pathology

Phagocytosis of Mycobacterium tuberculosis (Mtb) aggregates, rather than similar numbers of single bacilli, induces host macrophage death and favors bacterial growth. Here, we examined whether aggregation contributes to enhanced Mtb pathogenicity in vivo in rabbit lungs. Rabbits were exposed to infectious aerosols containing mainly Mtb-aggregates (Mtb-AG) or Mtb-single cells (Mtb-SC). The lung bacterial load, histology, and immune cell composition were investigated over time. Genome-wide transcriptome analysis, cellular and tissue-level assays, and immunofluorescent imaging were performed on lung tissue to define and compare differential immune activation and pathogenesis between Mtb-AG and Mtb-SC infection. Lung bacillary loads, disease scores, lesion size, and structure were significantly higher in Mtb-AG than in Mtb-SC infected animals. A differential immune cell distribution and activation were noted in the lungs and spleen of the two groups of infected animals. Mtb-AG infected animals also showed early induction of inflammatory network genes associated with necrosis and reduced host cell viability. Consistently, larger lung granulomas with clumped Mtb, extensive necrotic foci, and elevated matrix metalloproteases expression were observed in Mtb-AG infected rabbits. Our findings suggest that bacillary aggregation increases Mtb fitness for improved growth and accelerated lung inflammation and cell death, thereby exacerbating disease pathology in the lungs.

microbiology↗

bioRxiv2021

A pipeline for systematic comparison of model levels and parameter inference settings applied to negative feedback gene regulation

Quantitative stochastic models of gene regulatory networks are important tools for studying cellular regulation. Such models can be formulated at many different levels of fidelity. A practical challenge is to determine what model fidelity to use in order to get accurate and representative results. The choice is important, because models of successively higher fidelity come at a rapidly increasing computational cost. In some situations, the level of detail is clearly motivated by the question under study. In many situations however, many model options could qualitatively agree with available data, depending on the amount of data and the nature of the observations. Here, an important distinction is whether we are interested in inferring the true (but unknown) physical parameters of the model or if it is sufficient to be able to capture and explain available data. The situation becomes complicated from a computational perspective because inference and model selection need to be approximate. Most often it is based on likelihood-free Approximate Bayesian Computation (ABC) and here determining which summary statistics to use, as well as how much data is needed to reach the desired level of accuracy, are difficult tasks. Ultimately, all of these aspects - the model fidelity, the available data, and the numerical choices for inference and model selection - interplay in a complex manner. In this paper we develop a computational pipeline designed to systematically evaluate inference accuracy for a wide range of true known parameters. We then use it to explore inference settings for negative feedback gene regulation. In particular, we compare a spatial stochastic model, a coarse-grained multiscale model, and a simple well-mixed model for several data-scenarios and for multiple numerical options for parameter inference. Practically speaking, this pipeline can be used as a preliminary step to guide modelers prior to gathering experimental data. By training Gaussian processes to approximate the distance metric, we are able to significantly reduce the computational cost of running the pipeline.

systems biology↗

bioRxiv2021

Disentangling the effects of past logging and ongoing cryptic anthropogenic disturbance on vegetation structure and composition in Himalayan Foothills, India

Most tropical forests have undergone commercial logging. Even where logging has ceased, subsistence harvest of forest resources often persists especially in South-East Asia. Understanding of impacts of frequent forest resources extraction in areas recovering from past selective logging would be essential for designing the appropriate management interventions. We studied the impacts of current chronic anthropogenic disturbances (hereafter CAD) and past selective logging on vegetation structure, diversity, and regeneration, and the invasion of a non-native shrub, Lantana camara, in three major forest types in the Himalayan foothills, India. We analyzed field data on intensity of CAD and vegetation variables, collected from 269 stratified random plots, using ordination and generalized linear (mixed) modeling approaches. Our results, based on 2758 adult trees of 54 species, showed that forest types differed in disturbance regimes depending on protection level and availability of fodder tree species. Intensity of CAD depended on proximity to settlements (for livestock related disturbances). Whereas selective logging, including firewood collection, was associated with land protection status. Selective logging reduced the extent of mature forest but facilitated regeneration, thereby promoting secondary forest features such as tree density and canopy cover. In contrast, the interaction between lopping and selective logging was negatively associated with regeneration. Past logging facilitated L. camara invasion in Dry and Hill forests but not in Moist forest. Finally, while selective logging marginally enhanced tree diversity, CAD reduced native shrub diversity. Our study demonstrates that selective logging followed by CAD arrest forest recovery, as evident from the suppression of mature forest elements, loss of shrub biomass, reduced regeneration rate, and facilitation of invasive species. To abate these impacts, alternative livelihood/subsistence options that sustain forests and local communities should be explored. Additionally, CAD management should be site-specific as local ecological contexts modify their impacts on forests.

ecology↗

bioRxiv2021

Immunophenotyping and transcriptional profiling of human plasmablasts in dengue.

Previous studies have shown that plasmablasts expand massively in dengue patients as compared to many other situations such as influenza infection or vaccination. However, a detailed understanding of the phenotypes and transcriptional features of these cells is lacking. Moreover, despite India having nearly a third of global dengue disease burden, there is virtually no information on plasmablasts responses in dengue patients from India. Here, we provide a detailed characterization of plasmablast responses from dengue confirmed febrile children in India. Immunophenotyping and RNA seq analysis showed that in addition to secreting dengue specific antibodies, these massively expanding cells expressed several adhesion molecules, chemokines and chemokine receptors that are involved in endothelial interactions, homing to skin or mucosal tissues including intestine. Surprisingly, we found that these cells also upregulated expression of several cytokine genes that are involved in angiogenesis, leukocyte extravasation and vascular permeability. These transcriptional features were qualitatively similar to plasmablasts from influenza vaccinees. Interestingly, the expansion of the plasmablasts in dengue patients was significantly lower in patients with primary dengue infection compared to those with secondary dengue. Moreover, within the primary dengue patients, their expansion was significantly lower in patients with mild dengue infection (DI) compared to patients with dengue with warning signs (DW) or severe dengue (SD). These results significantly improve our understanding of human plasmablast responses in dengue. Importance Dengue is a globally spreading with over 100 million clinical cases annually with symptoms ranging from mild self-limiting febrile illness to more severe and sometimes life-threatening dengue hemorrhagic fever or shock, especially among children. India contributes nearly a third of global dengue disease burden. The pathophysiology of dengue is complex and remains poorly understood despite many advances indicating a key role for antibody dependent enhancement of infection. While serum antibodies have been extensively studied, the characteristics of the cellular factories responsible for antibody production, i.e., plasmablasts, are only beginning to emerge. This study provides a comprehensive understanding of the magnitude, phenotype, functional and transcriptional profiles of human plasmablasts from dengue patients in India.

immunology↗

bioRxiv2021

Effective Therapy Targeting Cytochrome bc1 Prevents Babesia Erythrocytic Development and Protects from Lethal Infection

Targeting conserved metabolic processes that are essential for viability of pathogens, such as Plasmodium and Babesia that cause blood-borne diseases, is an effective strategy to eliminate malaria and babesiosis infections with no recrudescence. One interesting target is the mitochondrial cytochrome bc1 complex, which could be inhibited by drugs such as endochin-like quinolones (ELQ) and atovaquone. We used the tick-transmitted and culturable blood-borne pathogen Babesia duncani to evaluate the structure-activity relationship, safety, efficacy and mode of action of ELQs. We identified a potent and highly selective ELQ prodrug (ELQ-502), which alone or in combination with atovaquone eliminates B. microti and B. duncani infections in vitro and in mouse models of parasitemia and lethal infection. The strong efficacy at low dose, excellent safety, bioavailability and long half-life of this experimental therapy makes it an ideal clinical candidate for the treatment of human infections caused by Babesia and its closely related apicomplexan parasites.

microbiology↗

bioRxiv2021

EHMT2 Controls Transcriptional Noise and the Developmental Switch after Gastrulation in the Mouse Embryo

Embryos that carry zygotic or parental mutations in Ehmt2, the gene encoding the main euchromatic histone H3K9 methyltransferase, EHMT2, exhibit variable developmental delay. We asked the question whether the delayed embryo is different transcriptionally from the normally developing embryo when they reach the same developmental stage. We collected embryos carrying a series of genetic deficiencies in the Ehmt2 gene and performed total RNA sequencing of somite stage-matched individual embryos. We applied novel four-way comparisons to detect differences between normal versus deficient embryos, and between 12-somite and 6-somite embryos. Importantly, we also identified developmental changes in transcription that only occur during the development of the normal embryo. We found that at the 6-somite stage, gastrulation-specific genes were not precisely turned off in the Ehmt2-/- embryos, and genes involved in organ growth, connective tissue development, striated muscle development, muscle differentiation, and cartilage development were not precisely switched on in the Ehmt2-/- embryos. Zygotic EHMT2 reduced transcriptional variation of developmental switch genes and at some repeat elements at the six-somite stage embryos. Maternal EHMT2-mutant embryos also displayed great transcriptional variation consistent with their variable survival, but transcription was normal in developmentally delayed parental haploinsufficient embryos, consistent with their good prospects. Global profiling of transposable elements in the embryo revealed that specific repeat classes responded to EHMT2. DNA methylation was specifically targeted by EHMT2 to LTR repeats, mostly ERVKs. Long noncoding transcripts initiated from those misregulated driver repeats in Ehmt2-/- embryos, and extended to several hundred kilobases, encompassing a multitude of additional, similarly misexpressed passenger repeats. These findings establish EHMT2 as an important regulator of the transition between gastrulation programs and organ specification programs and of variability.

developmental biology↗

bioRxiv2021

Intergenerational Effects of Early Life Starvation on Life-History, Consumption, and Transcriptomes of a Holometabolous Insect

Intergenerational effects, also known as parental effects in which the offspring phenotype is influenced by the parental phenotype, can occur in response to factors that occur not only in early but also in late parental life. However, little is known about how these parental life stage-specific environments interact with each other and with the offspring environment to influence offspring phenotype, particularly in organisms that realize distinct niches across ontogeny. We examined the effects of parental larval starvation and adult reproductive environment on offspring traits under matching or mismatching offspring larval starvation conditions using the holometabolous, haplo-diploid insect Athalia rosae (turnip sawfly). We show that the parental larval starvation treatment had trait-dependent intergenerational effects on both life-history and consumption traits of offspring larvae, partly in interaction with offspring conditions and sex, while there was no significant effect of parental adult reproductive environment. In addition, while offspring larval starvation led to numerous gene- and pathway-level expression differences, parental larval starvation impacted fewer genes and only the ribosomal pathway. Our findings reveal that parental starvation evokes complex intergenerational effects on offspring life-history traits, consumption patterns as well as gene expression, although the effects are less pronounced than those of offspring starvation.

ecology↗

bioRxiv2021

Identification and characterization of novel plasma proteins in drug resistant HIV/AIDS patients by SWATH-MS

Background and ObjectivesAcquired immunodeficiency syndrome is one of the most important diseases caused by human immunodeficiency virus. Understanding its molecular pathogenesis is essential to manage the disease at the population level. In this study, a quantitative analysis of plasma proteins was carried out in drug resistant and drug respondent patients using the SWATH-MS. MethodsSequential window acquisition of all theoretical mass spectra (SWATH-MS) is a prime technique to seek the key plasma proteins involved in virus replication and drug metabolism during therapy. ResultsIn total, 204 proteins were identified and quantified, 57 proteins were differentially expressed, 25 proteins were down regulated and 32 proteins were upregulated in drug resistant patients. Six proteins such as complement C4-A, immunoglobulin heavy variable 1-2, carboxylic ester hydrolase, fibulin-1, immunoglobulin lambda constant 7, secreted phosphoprotein 24 were statistically expressed in drug resistant patients compared to the drug respondent patients. Gene ontology study and protein-protein interaction networks were established in six statistically significant differentially expressed proteins of the drug resistant patients. Interpretation and ConclusionOur findings high lights the novel proteins that were differentially expressed in drug resistant patients. A label-free quantitative proteomics method for depleted human plasma samples by SWATH-MS that can be useful in plasma proteomics research in any biological system.

biochemistry↗

bioRxiv2021

Meta-analysis of scRNA seq data to define the landscape of human liver immune homeostasis.

The liver is unique in both its ability to maintain immune homeostasis and in its potential for immune tolerance following solid organ transplantation. Single-cell RNA sequencing (scRNA seq) is a powerful approach to generate highly dimensional transcriptome data to understand cellular phenotypes. However, when scRNA data is produced by different groups, with different data models, different standards, and samples processed in different ways, it can be challenging to draw meaningful conclusions from the aggregated data. The goal of this study was to establish a method to combine human liver scRNA seq datasets by 1) characterizing the heterogeneity between studies and 2) using the meta-atlas to define the dominant phenotypes across immune cell subpopulations in healthy human liver. Publicly available scRNA seq data generated from liver samples obtained from a combined total of 17 patients and [~]32,000 cells were analyzed. Liver-specific immune cells (CD45+) were extracted from each dataset, and immune cell subpopulations (myeloid cells, NK and T cells, plasma cells, and B cells) were examined using dimensionality reduction (UMAP), differential gene expression, and ingenuity pathway analysis. All datasets co-clustered, but cell proportions differed between studies. Gene expression correlation demonstrated similarity across all studies, and canonical pathways that differed between datasets were related to cell stress and oxidative phosphorylation rather than immune-related function. Next, a meta-atlas was generated via data integration and compared against PBMC data to define gene signatures for each hepatic immune subpopulation. This analysis defined key features of hepatic immune homeostasis, with decreased expression across immunologic pathways and enhancement of pathways involved with cell death. This method for meta-analysis of scRNA seq data provides a novel approach to broadly define the features of human liver immune homeostasis. Specific pathways and cellular phenotypes described in this human liver immune meta-atlas provide a critical reference point for further study of immune mediated disease processes within the liver.

immunology↗

bioRxiv2020

Integration of Magnetic Tweezers and Traction Force Microscopy for the Exploration of Matrix Rheology and Keratinocyte Mechanobiology: Model Force- and Displacement-Controlled Experiments

In this work we demonstrate the integration of magnetic tweezers (MT) with substrate deformation tracking microscopy (DTM) and traction force microscopy (TFM) for the investigation of extracellular matrix rheology and human epidermal keratinocyte mechanobiology in the context of human blistering skin diseases. Two model bead-on-gel experiments are described in which an MT device is used to apply a prescribed force or displacement waveform to a fibronectin-coated superparamagnetic bead attached to a type I collagen gel containing a layer of covalently attached red-fluorescent microspheres. Serial fast time-lapse DIC and epifluorescence image acquisitions are used to capture displacements of the bead and microspheres, respectively, in response to the applied force or displacement. Due to the large number of acquired images and the dynamic behavior of substrate microspheres observed during the experiment, new quantitative methods are developed for the tracking and filtering of microsphere displacement data, the selection of L2 regularization parameters used for TFM analysis, and the identification of time intervals within the overall image set that can be approximated as being subject to elastostatic conditions. Two major proof-of-concept applications are described in which integrated MT-DTM/TFM experiments are used to (i) estimate the elastic properties of a fibrillar type I collagen gel substrate and (ii) demonstrate how a force applied to a focal adhesion contact on the apical surface of a living keratinocyte is directly transmitted to basal cell-matrix anchoring junctions as observed by substrate deformations and incremental traction stresses that develop within the collagen subjacent to the cell.

biophysics↗

bioRxiv2020

Phenotypic plasticity of ER+ breast cancer in the bone microenvironment

ER+ breast cancer exhibits a strong bone-tropism in metastasis. How the bone microenvironment impacts the ER signaling and endocrine therapies remains poorly understood. Here, we discover that the osteogenic niche transiently reduces ER expression and activities specifically in bone micrometastases (BMMs), leading to endocrine resistance. This is mediated by gap junctions and paracrine FGF/PDGF signaling, which together generate a stable "memory": cancer cells extracted from bone remain resistant to endocrine therapies for several generations. Using single cell-derived populations (SCPs), we demonstrated that this process is independent of clonal selection, and represents an EZH2-mediated epigenomic reprogramming. EZH2 drives ER+ BMMs toward a basal and stem-like state. EZH2 inhibition reverses endocrine resistance. Our data demonstrates how epigenomic adaptation to the bone microenvironment drives phenotypic plasticity of metastatic seeds and alters their therapeutic responses together with clonal selection, and provides insights into the clinical enigma of ER+ metastatic recurrences despite endocrine therapies.

cancer biology↗

bioRxiv2020

Haploid, diploid, and pooled exome capture recapitulate features of biology and paralogy in two non-model tree species

Despite their suitability for studying evolution, many conifer species have large and repetitive giga-genomes (16-31Gbp) that create hurdles to producing high coverage SNP datasets that captures diversity from across the entirety of the genome. Due in part to multiple ancient whole genome duplication events, gene family expansion and subsequent evolution within Pinaceae, false diversity from the misalignment of paralog copies create further challenges in accurately and reproducibly inferring evolutionary history from sequence data. Here, we leverage the cost-saving benefits of pool-seq and exome-capture to discover SNPs in two conifer species, Douglas-fir (Pseudotsuga menziesii var. menziesii (Mirb.) Franco, Pinaceae) and jack pine (Pinus banksiana Lamb., Pinaceae). We show, using minimal baseline filtering, that allele frequencies estimated from pooled individuals show a strong positive correlation with those estimated by sequencing the same population as individuals (r > 0.948), on par with such comparisons made in model organisms. Further, we highlight the use of haploid megagametophyte tissue in identifying sites that are likely due to misaligned paralogs. Together with additional minor filtering, we show that it is possible to remove many of the loci with large frequency estimate discrepancies between individual and pooled sequencing approaches, improving the correlation further (r > 0.973). Our work addresses bioinformatic challenges in non-model organisms with large and complex genomes, highlights the use of megagametophyte tissue for the identification of paralog sites when sequencing large numbers of populations, and suggests the combination of pool-seq and exome capture to be robust for further evolutionary hypothesis testing in these systems.

genomics↗

bioRxiv2020

Variants in RABL2A causing male infertility and ciliopathy

PurposeApproximately 7% of men suffer from infertility worldwide and sperm abnormalities are the major cause. Though genetic defects are thought to underlie a substantial fraction of all male infertility cases, the actual molecular bases are usually undetermined. Because the consequences of most genetic variants in populations are unknown, this complicates genetic diagnosis even after genome sequencing of patients. Some patients with ciliopathies, including primary ciliary dyskinesia (PCD) and Bardet-Biedl syndrome (BBS), also suffer from infertility because sperm flagella, which share several characteristics with cilia, are also affected in these patients. MethodsTo identify infertility-causing genetic variants in human populations, we used in silico predictions to identify potentially deleterious SNP (single nucleotide polymorphism) alleles of RABL2A, a gene essential for normal cilia and flagella function. Candidate variants were assayed for protein stability in vitro, and the destabilizing variants were modeled in mice using CRISPR/Cas9-mediated genome editing. The resulting mice were characterized phenotypically for reproductive and developmental defects. ResultsTwo of the SNP alleles, Rabl2L119F (rs80006029) and Rabl2V158F (rs200121688), destabilized the protein. Mice bearing these alleles exhibited PCD- and BBS-associated disorders including male infertility, early growth retardation, excessive weight gain in adulthood, heterotaxia, pre-axial polydactyly, neural tube defects (NTD) and hydrocephalus. ConclusionOur study identified and validated pathogenicity of two variants causing ciliopathies and male infertility in human populations, and identified phenotypes not previously described for null alleles of Rabl2.

genetics↗

bioRxiv2020

High throughput detection and genetic epidemiology of SARS-CoV-2 using COVIDSeq next generation sequencing

The rapid emergence of coronavirus disease 2019 (COVID-19) as a global pandemic affecting millions of individuals globally has necessitated sensitive and high-throughput approaches for the diagnosis, surveillance and for determining the genetic epidemiology of SARS-CoV-2. In the present study, we used the COVIDSeq protocol, which involves multiplex-PCR, barcoding and sequencing of samples for high-throughput detection and deciphering the genetic epidemiology of SARS-CoV-2. We used the approach on 752 clinical samples in duplicates, amounting to a total of 1536 samples which could be sequenced on a single S4 sequencing flow cell on NovaSeq 6000. Our analysis suggests a high concordance between technical duplicates and a high concordance of detection of SARS-CoV-2 between the COVIDSeq as well as RT-PCR approaches. An in-depth analysis revealed a total of six samples in which COVIDSeq detected SARS-CoV-2 in high confidence which were negative in RT-PCR. Additionally, the assay could detect SARS-CoV-2 in 21 samples and 16 samples which were classified inconclusive and pan-sarbeco positive respectively suggesting that COVIDSeq could be used as a confirmatory test. The sequencing approach also enabled insights into the evolution and genetic epidemiology of the SARS-CoV-2 samples. The samples were classified into a total of 3 clades. This study reports two lineages B.1.112 and B.1.99 for the first time in India. This study also revealed 1,143 unique single nucleotide variants and added a total of 73 novel variants identified for the first time. To the best of our knowledge, this is the first report of the COVIDSeq approach for detection and genetic epidemiology of SARS-CoV-2. Our analysis suggests that COVIDSeq could be a potential high sensitivity assay for detection of SARS-CoV-2, with an additional advantage of enabling genetic epidemiology of SARS-CoV-2.

genomics↗

bioRxiv2020

CBX2 and CBX7 antagonistically regulate metabolic reprogramming in breast cancer

Striking similarity exists between metabolic changes associated with embryogenesis and tumorigenesis. Chromobox proteins-CBX2/4/6/7/8, core components of canonical polycomb repressor complex 1 (cPRC1), play essential roles in embryonic development and aberrantly expressed in breast cancer. Understanding how altered CBX expression relates to metabolic reprogramming in breast cancer may reveal vulnerabilities of therapeutic pertinence. Using transcriptomic and metabolomic data from breast cancer patients (N>3000 combined), we performed pathway-based analysis and identified outstanding roles of CBX2 and CBX7 in positive and negative regulation of glucose metabolism, respectively. Genetic ablation experiments validated the contrasting roles of two isoforms in cancer metabolism and cell growth. Furthermore, we provide evidence for the role of mTORC1 signaling in mediating contrary effects of CBX2 and CBX7 on breast cancer metabolism. Underpinning the biological significance of metabolic roles, CBX2 and CBX7 were found to be the most up- and down-regulated isoforms, respectively, in breast tumors compared to normal tissues. Moreover, CBX2 and CBX7 expression (not other isoforms) correlated strongly, but oppositely, with breast tumor subtype aggressiveness and the proliferation markers. Consistently, genomic data also showed higher amplification frequency of CBX2, not CBX7, in breast tumors. Highlighting the clinical significance of findings, disease-specific survival and drug sensitivity analysis revealed that CBX2 and CBX7 predicted patient outcome and sensitivity to FDA-approved clinical drugs. In summary, this work identifies novel cross-talk between CBX2/7 and breast tumor metabolism, and the results presented may have implications in strategies targeting breast cancer.

cancer biology↗

bioRxiv2020

Integrated genomic view of SARS-CoV-2 in India

India first detected SARS-CoV-2, causal agent of COVID-19 in late January-2020, imported from Wuhan, China. March-2020 onwards; importation of cases from rest of the countries followed by seeding of local transmission triggered further outbreaks in India. We used ARTIC protocol based tiling amplicon sequencing of SARS-CoV-2 (n=104) from different states of India using a combination of MinION and MinIT from Oxford Nanopore Technology to understand introduction and local transmission. The analyses revealed multiple introductions of SARS-CoV-2 from Europe and Asia following local transmission. The most prevalent genomes with patterns of variance (confined in a cluster) remain unclassified, here, proposed as A4-clade based on its divergence within A-cluster. The viral haplotypes may link their persistence to geo-climatic conditions and host response. Despite the effectiveness of non-therapeutic interventions in India, multipronged strategies including molecular surveillance based on real-time viral genomic data is of paramount importance for a timely management of the pandemic.

microbiology↗