Biology subjects
Publications and source records attributed to Basu, S..
Molecular tools for modulating transgene expression in Aedes aegypti are few. Here we demonstrate that adjustments to the AePUb promoter length can alter expression levels of two reporter proteins in Ae. aegypti cell culture and in mosquitoes. This provides a simple means for increasing or decreasing expression of a gene of interest and easy translation from cells to whole insects.
SNP heritability [Formula] is defined as the proportion of phenotypic variance explained by genotyped SNPs and is believed to be a lower bound of heritability (h2), being equal to it if all causal variants are genotyped. Despite the simple intuition behind [Formula], its interpretation and equivalence to h2 is unclear, particularly in the presence of admixture and assortative mating. Here we use analytical theory and simulations to describe the behavior of h2 and three widely used random-effect estimators of [Formula] Genome-wide restricted maximum likelihood (GREML), Haseman-Elston (HE) regression, and LD score regression (LDSC) - in admixed populations. We show that [Formula] estimates can be biased in admixed populations, even if all causal variants are genotyped and in the absence of confounding due to shared environment. This is largely because admixture generates directional LD, which contributes to the genetic variance, and therefore to heritability. Random-effect estimators of [Formula], because they assume that SNP effects are independent, do not capture the contribution, which can be positive or negative depending on the genetic architecture, leading to under- or over-estimates of [Formula] relative to h2. For the same reason, estimates of local ancestry heritability [Formula] are also biased in the presence of directional LD. We describe this bias in [Formula] and [Formula] as a function of admixture history and the genetic architecture of the trait, clarifying their interpretation and implication for genome-wide association studies and polygenic prediction in admixed populations.
Early-Onset Colorectal Carcinoma (EOCRC) is a growing concern as reports indicate a worldwide increase in the incidence of CRC among young adults (<50 years old). In an effort to understand the different mode of pathogenesis in young-onset CRC, we performed a pilot study wherein we looked at colorectal tumors from both young (< 50 years old) and old patients (>55 years old) and screened them to eliminate tumors positive for Microsatellite Instability (MSI) and showing activation of the Wnt pathway, known canonical factors in CRC pathogenesis. RNA isolated from EOCRC and Late-Onset (LOCRC) tumors and paired normal tissues without MSI, nuclear {beta}-catenin and APC mutations were sent for small RNA seq to identify miRNA alterations between the two subsets. Comparative analysis revealed differential expression of 23 miRNAs specific to EOCRC and 11 miRNAs specific to LOCRC. We validated the top 10 EOCRC DEMs in TCGA-COAD cohorts followed by validation in additional EOCRC and LOCRC cohorts. Our integrated analysis revealed upregulation of hsa-miR-1247-3p, hsa-miR-148a-3p and hsa-miR-27a-5p and downregulation of hsa-miR-326 between the two subsets. Experimentally validated targets of the above miRNAs were compared with differentially expressed genes in the TCGA dataset to identify targets with physiological significance in EOCRC development. Our analysis revealed downregulation of epithelial gene expression and intercellular junction proteins potentially leading to dissolution of epithelial intercellular junctions in EOCRC development and EMT progression. Upregulated targets included genes whose expression have been reported to correlate with CRC tumor invasion, liver metastasis, disease recurrence and poor prognosis.
Genetic manipulation of Aedes aegypti is key to developing a deeper understanding of this insects biology, vector-virus interactions and makes future genetic control strategies possible. Despite some advances, this process remains laborious and requires highly skilled researchers and specialist equipment. Here we present two improved methods for genetic manipulation in this species. Use of transgenic lines which express Cre recombinase allowed, by simple crossing schemes, germline or somatic recombination of transgenes, which could be utilized for numerous genetic manipulations. PhiC31 integrase based methods for site-specific integration of genetic elements was also improved, by developing a plasmid which expresses PhiC31 when injected into early embryos, eliminating the need to use costly and unstable mRNA as is the current standard.
Pathogenesis of inflammatory, chronic and common skin disease Psoriasis involves immune cells, skin cells (keratinocytes) and cytokines secreted by them. Hyperproliferation and abnormal differentiation of keratinocytes are believed to be a hallmark of it. Roles of several cytokines such as TNF, IL-15, IL-17 and IL-23 in Psoriasis have been explored through mathematical/computational models as well as experimentally. However, the role of pro-inflammatory cytokine IL-36 is still elusive, especially in the case of General Pustular Psoriasis, a prevalent type of Psoriasis. To explore the role of that here, we construct a network embodying indirect cell-cell interactions of a few immune and skin cells mediated by IL-36 based on the existing knowledge. Further, we develop a mathematical model for the network and study the steady-state behaviour of that. Our results demonstrate that an increase in the level of IL-36 could lead to the hyper-proliferation of keratinocytes and, thus, Psoriasis. In addition, the analysis suggests that the plaque formation and progression of Psoriasis could occur via a gradual or switch-like increase in the population of keratinocytes. The switch-like increase would be due to the bistable behaviour of the network and could be used as a novel treatment strategy, as proposed and demonstrated earlier.
Head and neck squamous cell carcinomas (HNSCC) are the seventh most common cancer and represent a global health burden. Immune checkpoint inhibitors (ICIs) have shown promise in treating recurrent/metastatic cases, with durable benefit in [~]30% of patients. Current biomarkers for head and neck tumors are limited in their dynamic ability to capture tumor microenvironment (TME) features, with an increasing need for deeper tissue characterization. Therefore, new biomarkers are needed to accurately stratify patients and predict responses to therapy. Here, we have optimized and applied an ultra-high plex, single-cell spatial protein analysis in HNSCC. Tissues were simultaneously analyzed with a panel of 101 antibodies that targeted biomarkers related to tumor immune, metabolic and stress microenvironments. Our data uncovered a high degree of intra-tumoral heterogeneity intrinsic to head and neck tumors and provided unique insights into the biology of the tumor. In particular, a cellular neighborhood analysis revealed the presence of 6 unique spatial tumor-immune neighborhoods enriched in functionally specialized immune cell subsets across the patient tissue. Additionally, functional phenotyping based on key metabolic and stress markers identified four distinct tumor regions with differential protein signatures. One tumor region was marked by infiltration of CD8+ cytotoxic T cells and overexpression of BAK, a proapoptotic regulator, suggesting strong immune activation and stress. Another adjacent region within the same tumor had high expression of G6PD and MMP9, known drivers of tumor resistance and invasion respectively. This dichotomy of immune activation-induced death and tumor progression in the same sample demonstrates the heterogenous niches and competing microenvironments that underpin clinical responses of therapeutic resistance. Our data integrate single-cell ultra-high plex spatial information with the functional state of the tumor microenvironment to provide insights into a partial response to immune checkpoint inhibitor therapy in HNSCC. We believe that the approach outlined in this study will pave the way towards a new understanding of TME features associated with response and sensitivity to ICI therapies.
Large scale protein-protein interaction (PPI) network of an organism provides key insights into its cellular and molecular functionalities, signaling pathways and underlying disease mechanisms. For any organism the total number of unexplored protein interactions significantly outnumbers all known positive and negative interactions. For Human, all known PPI datasets, contain only [~] 5.61 million positive and [~] 0.76 million negative interactions, that together is [~] 3.1% of potential interactions. Moreover, conventional PPI prediction methods produce binary results. At the same time, recent studies show that protein binding affinities may prove to be effective in detecting protein complexes, disease association analysis, signaling network reconstruction, etc. Keeping these in mind, we present a fuzzy semantic scoring function using the Gene Ontology (GO) graphs to assess the binding affinity between any two proteins at an organism level. We have implemented a distributed algorithm in Apache Spark that computes this function and used it to process a Human PPI network of [~] 180 million potential interactions resulting from 18 994 reviewed proteins for which GO annotations are available. The quality of the computed scores has been validated with respect to the available state-of-the-art methods on benchmark data sets. The resulting scores are published with a web-server for non-commercial use at: http://fuzzyppi.mimuw.edu.pl/.
Cytochrome c oxidase (CcO) is a large membrane-bound hemeprotein that catalyzes the reduction of dioxygen to water. Unlike classical dioxygen binding hemeproteins with a heme b group in their active sites, CcO has a unique binuclear center (BNC) comprised of a copper atom (CuB) and a heme a3 iron, where O2 binds and is reduced to water. CO is a versatile O2 surrogate in ligand binding and escape reactions. Previous time-resolved spectroscopic studies of the CO complexes of bovine CcO (bCcO) revealed that photolyzing CO from the heme a3 iron leads to a metastable intermediate (CuB-CO), where CO is bound to CuB, before it escapes out of the BNC. Here, with a time-resolved serial femtosecond X-ray crystallography-based pump-probe method, we detected a geminate photoproduct of the bCcO-CO complex, where CO is dissociated from the heme a3 iron and moved to a temporary binding site midway between the CuB and the heme a3 iron, while the locations of the two metal centers and the conformation of the Helix-X, housing the proximal histidine ligand of the heme a3 iron, remain in the CO complex state. This new structure, combined with other reported structures of bCcO, allows the full definition of the ligand dissociation trajectory, as well as the associated protein dynamics.
A microbial community maintains its ecological dynamics via metabolite crosstalk. Hence knowledge of the metabolome, alongside its populace, would help us understand the functionality of a community and also predict how it will change in atypical conditions. Methods that employ low-cost metagenomic sequencing data can predict the metabolic potential of a community, that is, its ability to produce or utilize specific metabolites. These, in turn, can potentially serve as markers of biochemical pathways that are associated with different communities. We developed MMIP (Microbiome Metabolome Integration Platform), a web-based analytical and predictive tool that can be used to compare the taxonomic content, diversity variation and the metabolic potential between two sets of microbial communities from targeted amplicon sequencing data. MMIP is capable of highlighting statistically significant taxonomic, enzymatic and metabolic attributes as well as learning-based features associated with one group in comparison with another. Further MMIP can predict linkages among species or groups of microbes in the community, specific enzyme profiles, compounds or metabolites associated with such a group of organisms. With MMIP, we aim to provide a user-friendly, online web-server for performing key microbiome-associated analyses of targeted amplicon sequencing data, predicting metabolite signature, and using learning-based linkage analysis, without the need for initial metabolomic analysis, and thereby helping in hypothesis generation.
The photosynthetic and diazotrophic cyanobacterium Trichodesmium is a key contributor to marine biogeochemical cycles in the subtropical-oligotrophic oceans. Trichodesmium forms colonies that harbor a distinct microbial community, which expands their functional potential and is predicted to influence the cycling of carbon, nitrogen, phosphorus and iron (C, N, P, and Fe). To link key traits to taxa and elucidate how community structure influences nutrient cycling, we assessed Red Sea Trichodesmium colonies using metagenomics and metaproteomics. This diverse consortium comprises bacteria that typically associate with algae and particles, such as the ubiquitous Alteromonas macleodii, but also lineages specific to Trichodesmium, such as members from the order Balneolales. These bacteria carry functional traits that would influence resource cycling in the consortium, including siderophore biosynthesis, reduced phosphorus metabolism, vitamins, denitrification, and dissimilatory-nitrate-reduction-to-ammonium (DNRA) pathways. Denitrification and DNRA appeared to be modular as bacteria collectively completed the steps for these pathways. The vast majority of associated bacteria were auxotrophic for vitamins, indicating the interdependency of consortium members. Trichodesmium in turn may rely on associated bacteria to meet its high Fe demand as several lineages can synthesize the photolabile siderophores vibrioferrin, rhizoferrin, and petrobactin, enhancing the bioavailability of particulate-Fe to the entire consortium. Our results highlight that Trichodesmium is a hotspot for C, N, P, Fe, and vitamin exchange. The functional redundancy of nutrient cycling in the consortium likely underpins its resilience within an ever-changing global environment. ImportanceColonies of the cyanobacteria Trichodesmium act as a biological hotspot for the usage and recycling of key resources such as C, N, P and Fe within an otherwise oligotrophic environment. While Trichodesmium colonies are known to interact with a unique community of algae and particle-associated microbes, our understanding of the taxa that populate these colonies and the gene functions they encode is still limited. Characterizing the taxa and adaptive strategies that influence consortium physiology and its concomitant biogeochemistry is critical in a future ocean predicted to have increasing particulate fluxes and resource-depleted regions.
Prenatal and early life exposure to cigarette smoke (CS) have repeatedly been shown to induce stable, long-term changes in DNA methylation (DNAm) in offspring. It has been hypothesized that these changes might be functionally related to the known outcomes of prenatal and early life CS exposure, which include impaired lung development, altered lung function and increased risk of asthma and wheeze. However, to date, few studies have examined DNAm changes induced by prenatal CS in tissues of the lung, and even fewer have attempted to examine the specific influences of prenatal versus early postnatal exposures. Here, we have established a mouse model of CS exposure which isolates the effects of prenatal and early postnatal CS exposures in early life. We have used this model to measure the effects of prenatal and/or postnatal CS exposures on lung function and immune cell infiltration as well as DNAm and expression of Cyp1a1, a candidate gene previously observed to demonstrate DNAm differences upon CS exposure in humans. Our study revealed that exposure to CS prenatally and in the early postnatal period cause long-lasting differences in offspring lung function, gene expression and lung Cyp1a1 DNAm, which wane over time but are reestablished upon re-exposure to CS in adulthood. This study creates a testable mouse model which can be used to investigate the effects of prenatal and early postnatal CS exposures and will contribute to the design of intervention strategies to mediate these detrimental effects.
Mitogen-activated protein kinase (MAPK) pathways regulate multiple cellular responses, including the response to stress and cell differentiation, and are highly conserved across eukaryotes from yeast to humans. In yeast, the canonical activation of several MAPK pathways includes the interaction of the small GTPase Cdc42p with the p21-activated kinase (PAK) Ste20p. We recently found that the active conformation of Cdc42p is regulated by turnover, which impacts the activity of the pathway that regulates filamentous growth (fMAPK). Here, we show that Ste20p is turned over by the 26S proteasome. Ste20p was stabilized when bound to Cdc42p, presumably to sustain MAPK pathway signaling. Ste20p is a major conduit by which signals flow through the fMAPK pathway; however, by genetic approaches we also identified a Ste20p-independent branch of the fMAPK pathway. Ste20p-dependent signaling required the 14-3-3 proteins, Bmh1p and Bmh2p, while Ste20p-independent signaling required the fMAPK pathway adaptor and Cdc42p-interacting protein, Bem4p. Ste20p-independent signaling was inhibited by one of the GTPase-activating proteins for Cdc42p in the fMAPK pathway, Rga1p, which also dampened basal but not active fMAPK pathway activity. Finally, the polarity adaptor and Cdc42p-interacting protein, Bem1p, which also regulates the fMAPK pathway, interacts with the tetra-span protein Sho1p, connecting a sensor at the plasma membrane to a protein that regulates the GTPase module. Collectively, these data reveal new regulatory features surrounding a Rho-PAK module that may extend to other pathways that control cell differentiation.
ContextProtein-protein interaction (PPI) is a key component linked to virtually all cellular processes. Be it an enzyme catalysis ( classic type functions of proteins) or a signal transduction ( non-classic), proteins generally function involving stable or quasi-stable multi-protein associations. The physical basis for such associations is inherent in the combined effect of shape and electrostatic complementarities (Sc, EC) of the interacting protein partners at their interface, which provides indirect probabilistic estimates of the stability and affinity of the interaction. While Sc is a necessary criterion for inter-protein associations, EC can be favorable as well as disfavored (e.g., in transient interactions). Estimating equilibrium thermodynamic parameters ({Delta}Gbinding, Kd) by experimental means is costly and time consuming, thereby opening windows for computational structural interventions. Attempts to empirically probe {Delta}Gbinding from coarse-grain structural descriptors (primarily, surface area based terms) have lately been overtaken by physics-based, knowledge-based and their hybrid approaches (MM/PBSA, FoldX etc.) that directly compute {Delta}Gbinding without involving intermediate structural descriptors. MethodsHere we present EnCPdock (www.scinetmol.in/EnCPdock/), a user-friendly web-interface for the direct conjoint comparative analyses of complementarity and binding energetics in proteins. EnCPdock returns an AI-predicted {Delta}Gbinding computed by combining complementarity (Sc, EC) and other high-level structural descriptors (input feature vectors), and, renders a prediction accuracy comparable to the state-of-the-art. EnCPdock further locates a PPI complex in terms of its {Sc, EC} values (taken as an ordered pair) in the two-dimensional Complementarity Plot (CP). In addition, it also generates mobile molecular graphics of the interfacial atomic contact network for further analyses. EnCPdock also furnishes individual feature trends along with the relative probability estimates (Prfmax) of the obtained feature-scores with respect to the events of their highest observed frequencies. Together, these functionalities are of real practical use for structural tinkering and intervention as might be relevant in the design of targeted protein-interfaces. Combining all its features and applications, EnCPdock presents a unique online tool that should be beneficial to structural biologists and researchers across related fraternities.
Intracellular Salmonella resides and multiplies in cholesterol-rich specialized compartment called Salmonella-containing vacuoles (SCVs) and avoids fusion with acidic lysosomes. Given, lysosomes are primary organelle that redistributes LDL derived cholesterol to other organelles; we questioned how lysosomal cholesterol can be transported to SCV. We demonstrate here that peroxisomes are recruited to SCVs in human primary macrophages, epithelial cells and functions as pro-bacterial organelles. Further, this interaction is assisted by SseI, a Salmonella effector protein containing mammalian peroxisome targeting sequence. SseI localizes to peroxisome, interacts and activates a host Ras GTPase, ARF-1 on the peroxisome membrane. Activation of ARF-1 leads to recruitment of phosphatidylinsolitol-5- phosphate-4 kinase to generate phosphatidylinsolitol-4-5-bisphosphate on peroxisomes. Accordingly, the{Delta} sseI strain showed reduced virulence in cell lines and during mice infection. Taken together, our work identified a fascinating mechanism by which a pathogen targets host organelles via its secretory effectors and exploits host metabolic intermediates for its intracellular proliferation.
Zika virus (ZIKV) is a recently re-emerged flavivirus transmitted primarily through the bite of an infected mosquito, Aedes aegypti being the main vector. ZIKV infection is associated with a range of adverse effects; infection during pregnancy can lead to foetal abnormalities, including microcephaly. Lacking a licensed vaccine, or specific therapeutics, control of ZIKV transmission focuses on vector control. However, in most transmission settings, current methods are insufficient to successfully control ZIKV, or other similarly-transmitted arboviruses such as dengue and chikungunya viruses. This has stimulated interest in genetics-based methods, either to reduce the number of mosquitoes ("population suppression"), or to make mosquitoes less able to transmit ("population modification"). Here, we describe a method to selectively eliminate infected mosquitoes, using a virus sensor inserted into the mosquito genome and coupled to a quorum-counting lethal effector. In mosquitoes, ZIKV normally establishes persistent, lifelong infection; survival of these infected mosquitoes is crucial to transmission potential. Correspondingly, removal of infected mosquitoes can reduce vectorial capacity of a mosquito population, i.e. ability to transmit. Since relatively few mosquitoes become infected, typically <2%, engineered hypersensitivity to ZIKV would have only a modest population-level fitness cost, and lower still if transmission were successfully reduced by such means.
Glycerophospholipids including phosphatidylethanolamine (PE) and phosphatidylcholine (PC) are vital components of biological membranes. Trypanosomatid parasites of the genus Leishmania can acquire PE and PC via de novo synthesis and the uptake/remodeling of host lipids. In this study, we investigated the ethanolaminephosphate cytidyltransferase (EPCT) in Leishmania major, which is the causative agent for cutaneous leishmaniasis. EPCT is a key enzyme in the ethanolamine branch of the Kennedy pathway which is responsible for the de novo synthesis of PE. Our results demonstrate that L. major EPCT is a cytosolic protein capable of catalyzing the formation of CDP-ethanolamine from ethanolamine-phosphate and cytidine triphosphate. Genetic manipulation experiments indicate that EPCT is essential in both the promastigote and amastigote stages of L. major as the chromosomal null mutants cannot survive without the episomal expression of EPCT. This differs from our previous findings on the choline branch of the Kennedy pathway (responsible for PC synthesis) which is required only in promastigotes but not amastigotes. While episomal EPCT expression does not affect promastigote proliferation under normal conditions, it leads to reduced production of ethanolamine plasmalogen or plasmenylethanolamine, the dominant PE subtype in Leishmania. In addition, parasites with epsiomal EPCT exhibit heightened sensitivity to acidic pH and starvation stress, and significant reduction in virulence. In summary, our investigation demonstrates that proper regulation of EPCT expression is crucial for PE synthesis, stress response, and survival of Leishmania parasites throughout their life cycle. AUTHOR SUMMARYIn nature, Leishmania parasites alternate between fast replicating, extracellular promastigotes in sand fly gut and slow growing, intracellular amastigotes in macrophages. Previous studies suggest that promastigotes acquire most of their lipids via de novo synthesis whereas amastigotes rely on the uptake and remodeling of host lipids. Here we investigated the function of ethanolaminephosphate cytidyltransferase (EPCT) which catalyzes a key step in the de novo synthesis of phosphatidylethanolamine (PE) in Leishmania major. Results showed that EPCT is indispensable for both promastigotes and amastigotes, indicating that de novo PE synthesis is still needed at certain capacity for the intracellular form of Leishmania parasites. In addition, elevated EPCT expression alters overall PE synthesis and compromises parasites tolerance to adverse conditions and is deleterious to the growth of intracellular amastigotes. These findings provide new insight into how Leishmania acquire essential phospholipids and how disturbance of lipid metabolism can impact parasite fitness.
In this study, we introduce PIGEON--a novel statistical framework for quantifying and estimating polygenic gene-environment interaction (GxE) using a variance component analytical approach. Based on PIGEON, we outline the main objectives in GxE studies, demonstrate the flaws in existing GxE approaches, and introduce an innovative estimation procedure which only requires summary statistics as input. We demonstrate the statistical superiority of PIGEON through extensive theoretical and empirical analyses and showcase its performance in multiple analytic settings, including a quasi-experimental GxE study of health outcomes, gene-by-sex interaction for 530 traits, and gene-by-treatment interaction in a randomized clinical trial. Our results show that PIGEON provides an innovative solution to many long-standing challenges in GxE inference and may fundamentally reshape analytical strategies in future GxE studies.
Non-small cell lung cancer (NSCLC) possess very low survival rate due to poor response to chemotherapy and late detection. Epithelial to mesenchymal transition (EMT) is regarded as a major contributor to drive metastasis during NSCLC progression. Towards this, transforming growth factor-beta 1 (TGF-{beta}1) is the key driver that endows cancer cells with increased aggressiveness. Recently, our group synthesized a series of Schiff base quercetin derivatives (QDs) and ascertained their effectiveness on EMT markers of A549 cell line. Our study evidenced that EMT process was counteracted via the partial activation of a nuclear hormone receptor, Peroxisome proliferator-activated receptor (PPAR)-{gamma} through QDs. Hence, here we extended our work to investigate the interplay between PPAR-{gamma} partial activation by synthesized QDs, TGF-{beta}1-induced EMT and migration in human lung cancer A549 cells. The results revealed that TGF-{beta}1 played a critical role in suppressing PPAR-{gamma}, which was markedly reversed and increased by partial agonists; QUE2FH and QUESH at both protein and transcriptional level. Compared to full agonists, rosiglitazone could not elevate PPAR-{gamma} expression in the presence of TGF-{beta}1 and had negligible effect on translocation of PPAR-{gamma} to nucleus. The partial agonists not only stimulated PPAR-{gamma} in balanced manner but also prevented the loss of E-cadherin and acquisition of TGF-{beta}1-induced mesenchymal markers (Snail, Slug, Vimentin and Zeb-1). Subsequently, the effects were accompanied by attenuation of TGF-{beta}1-induced migratory ability of A549 cells. Together, with the balanced activation profile of PPAR-{gamma} ligands, our findings suggest that these novel partial agonists may serve as potential anti-cancer agents to impede metastasis.