Biology subjects

Das, P.

Publications and source records attributed to Das, P..

At least 91 records · Page 5Linked to original sources

bioRxiv2022

Differential contributions of nuclear lamina association and genome compartmentalization to gene regulation

Interactions of chromatin with the nuclear lamina play a significant role in properly organizing the genome in 3D space and in regulating gene expression. Genome wide studies have inferred the global association between the lamina, heterochromatin, gene repression and the B genomic compartment, and repositioning genes to the lamina can result in their repression. However, there are scenarios in which these features are discordant and, in those cases, the relative contribution to gene regulation of genomic compartment, chromatin, and lamin association status can be examined. Here we compared datasets from cell lines representing different states of differentiation across different cell type lineages to examine the relationships between changes in genomic compartmentalization, lamin association, and gene expression. With these data, we could examine, for example, what gene expression changes occur when a B compartment region is moved from the nuclear interior to the nuclear lamina and what differences exist between lamin associated and internal A compartment regions. In general, we observed an additive rather than redundant effect in which lamin association and compartment status both contribute to gene expression state. However, we found that cell type lineages differed in whether compartment status or lamin association had a dominant influence on gene expression. Finally, we identified conserved trends of how compartment and lamin association status influence the likelihood that gene expression will be induced or repressed in response to a physiochemical treatment.

genomics↗

bioRxiv2022

Transcriptional profiling of Hutchinson-Gilford Progeria syndrome fibroblasts reveals deficits in mesenchymal stem cell commitment to differentiation related to early events in endochondral ossification.

Hutchinson-Gilford Progeria Syndrome results from a mutation in Lamin A, and it is characterized by the incorporation of progerin into the nuclear lamina. Progerin expression leads to alterations in genome architecture, nuclear morphology, and epigenetic states, which in turn cause altered phenotypes in all cells of the mesenchymal lineage. Here, we report a comprehensive analysis of the transcriptional status of patient derived HGPS fibroblasts, including nine cell lines not previously reported. We observe that these fibroblasts carry abnormal transcriptional signatures, centering around five main functional hubs: DNA maintenance and epigenetics, bone development and homeostasis, blood vessel maturation and development, fat deposition and lipid management, and processes related to muscle growth. Stratification of patients by age revealed that a cohort of genes related to endochondral ossification and chondrogenic commitment show altered expression patterns in children aged four to seven years old, where this differentiation program starts in earnest, related to the growth of long bones. We further report changes in lamin associated domains and 3D genome organization around a cohort of genes of interest, identified in this study.

genomics↗

bioRxiv2022

Prefrontal cortex melanocortin 4 receptors (MC4R) mediate food intake behavior in mice

BackgroundMelanocortin 4 receptor (MC4R) activity in the hypothalamus is crucial for regulation of metabolism and food intake. The peptide ligands for the MC4R are associated with feeding, energy expenditure, and also with complex behaviors that orchestrate energy intake and expenditure, but the downstream neuroanatomical and neurochemical targets associated with these behaviors are elusive. In addition to strong expression in the hypothalamus, the MC4R is highly expressed in the medial prefrontal cortex, a region involved in executive function and decision-making. MethodsUsing viral techniques in genetically modified mice combined with molecular techniques, we identify and describe the neuronal dynamics, and define the effects on feeding behavior of a novel population of MC4R expressing neurons in the infralimbic region of the cortex. ResultsHere, we describe a novel population of MC4R-expressing neurons in the infralimbic (IL) region of the mouse prefrontal cortex that are glutamatergic, receive input from melanocortinergic neurons of the arcuate hypothalamus, and project to multiple regions that coordinate appetitive responses to food-related stimuli. The neurons are depolarized by application of MC4R-specific peptidergic agonist, THIQ. Deletion of MC4R from the IL neurons causes increased food intake and body weight gain and impaired executive function in simple food-related behavior tasks. ConclusionTogether, these data suggest that MC4R neurons of the IL play a critical role in the regulation of food intake.

neuroscience↗

bioRxiv2022

NLGC: Network Localized Granger Causality with Application to MEG Directional Functional Connectivity Analysis

Identifying the directed connectivity that underlie networked activity between different cortical areas is critical for understanding the neural mechanisms behind sensory processing. Granger causality (GC) is widely used for this purpose in functional magnetic resonance imaging analysis, but there the temporal resolution is low, making it difficult to capture the millisecond-scale interactions underlying sensory processing. Magnetoencephalography (MEG) has millisecond resolution, but only provides low-dimensional sensor-level linear mixtures of neural sources, which makes GC inference challenging. Conventional methods proceed in two stages: First, cortical sources are estimated from MEG using a source localization technique, followed by GC inference among the estimated sources. However, the spatiotemporal biases in estimating sources propagate into the subsequent GC analysis stage, may result in both false alarms and missing true GC links. Here, we introduce the Network Localized Granger Causality (NLGC) inference paradigm, which models the source dynamics as latent sparse multivariate autoregressive processes and estimates their parameters directly from the MEG measurements, integrated with source localization, and employs the resulting parameter estimates to produce a precise statistical characterization of the detected GC links. We offer several theoretical and algorithmic innovations within NLGC and further examine its utility via comprehensive simulations and application to MEG data from an auditory task involving tone processing from both younger and older participants. Our simulation studies reveal that NLGC is markedly robust with respect to model mismatch, network size, and low signal-to-noise ratio, whereas the conventional two-stage methods result in high false alarms and mis-detections. We also demonstrate the advantages of NLGC in revealing the cortical network-level characterization of neural activity during tone processing and resting state by delineating task- and age-related connectivity changes.

neuroscience↗

bioRxiv2021

A combination of potently neutralizing monoclonal antibodies isolated from an Indian convalescent donor protects against the SARS-CoV-2 delta variant

Although efficacious vaccines have significantly reduced the morbidity and mortality due to COVID-19, there remains an unmet medical need for treatment options, which monoclonal antibodies (mAbs) can potentially fill. This unmet need is exacerbated by the emergence and spread of SARS-CoV-2 variants of concern (VOCs) that have shown some resistance to vaccine responses. Here we report the isolation of two highly potently neutralizing mAbs (THSC20.HVTR04 and THSC20.HVTR26) from an Indian convalescent donor, that neutralize SARS-CoV-2 VOCs at picomolar concentrations including the delta variant (B.1.617.2). These two mAbs target non-overlapping epitopes on the receptor-binding domain (RBD) of the spike protein thereby preventing the virus attachment to its host receptor, human angiotensin converting enzyme-2 (hACE2). Furthermore, the mAb cocktail demonstrated protection against the Delta variant at low antibody doses when passively administered in the K18 hACE2 transgenic mice model, highlighting their potential as cocktail for prophylactic and therapeutic applications. Developing the capacity to rapidly discover and develop mAbs effective against highly transmissible pathogens like coronaviruses at a local level, especially in a low- and middle-income country (LMIC) such as India, will enable prompt responses to future pandemics as an important component of global pandemic preparedness. HighlightsO_LIIdentification of an Indian convalescent donor prior to emergence of SARS-CoV-2 Delta variant whose plasma demonstrated neutralization breadth across SARS-CoV-2 variants of concern (VOCs). C_LIO_LITwo (THSC20.HVTR04 and THSC20.HVTR26) monoclonal antibodies isolated from peripheral memory B cells potently neutralize SARS-CoV-2 VOCs: Alpha, Beta, Gamma, Delta and VOIs: Kappa and Delta Plus. C_LIO_LITHSC20.HVTR04 and THSC20.HVTR26 target non-competing epitopes on the receptor binding domain (RBD) and represent distinct germline lineages. C_LIO_LIPassive transfer of THSC20.HVTR04 and THSC20.HVTR26 mAbs demonstrated protection against Delta virus challenge in K18-hACE2 mice at low antibody doses. C_LI Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=142 SRC="FIGDIR/small/474152v1_ufig1.gif" ALT="Figure 1"> View larger version (31K): org.highwire.dtl.DTLVardef@1f1b55corg.highwire.dtl.DTLVardef@1b9b438org.highwire.dtl.DTLVardef@e6d2a6org.highwire.dtl.DTLVardef@f92cd_HPS_FORMAT_FIGEXP M_FIG C_FIG

immunology↗

bioRxiv2021

Characterizing the variation in chromosome structure ensembles in the context of the nuclear microenvironment

Inside the nucleus, chromosomes are subjected to direct physical interaction between different components, active forces, and thermal noise, leading to the formation of an ensemble of three-dimensional structures. However, it is still not well understood to what extent and how the structural ensemble varies from one chromosome region or cell-type to another. We designed a statistical analysis technique and applied it to single-cell chromosome imaging data to reveal the heterogeneity of individual chromosome structures. By analyzing the resulting structural landscape, we find that the largest dynamic variation is the overall radius of gyration of the chromatin region, followed by domain reorganization within the region. By comparing different human cell-lines and experimental perturbation data using this statistical analysis technique and a network-based similarity quantification approach, we identify both cell-type and condition-specific features of the structural landscapes. We identify a relationship between epigenetic state and the properties of chromosome structure fluctuation and validate this relationship through polymer simulations. Overall, our study suggests that the types of variation in a chromosome structure ensemble are cell-type as well as region-specific and can be attributed to constraints placed on the structure by factors such as variation in epigenetic state.

genomics↗

bioRxiv2021

The influence of new SARS-CoV-2 variant Omicron (B.1.1.529) on vaccine efficacy, its correlation to Delta Variants: a computational approach

The newly discovered COVID variant B.1.1.529 in Botswana has more than 30 mutations in spike and many other in non-spike proteins, far more than any other SARS-CoV-2 variant accepted as a variant of concern by the WHO and officially named Omicron, and has sparked concern among scientists and the general public. Our findings provide insights into structural modification caused by the mutations in the Omicrons receptor-binding domain and look into the effects on interaction with the hosts neutralising antibodies CR3022, B38, CB6, P2B-2F6, and REGN, as well as ACE2R using an in silico approach. We have employed secondary structure prediction, structural superimposition, protein disorderness, molecular docking, and MD simulation to investigate host-pathogen interactions, immune evasion, and transmissibility caused by mutations in the RBD region of the spike protein of the Omicron variant and compared it to the Delta variants (AY.1, AY.2, & AY.3) and wild type. Computational analysis revealed that the Omicron variant has a higher binding affinity for the human ACE2 receptor than the wild and Delta (AY.1 and AY.2 strains), but lower than the Delta AY.3 strain. MD simulation and docking analysis suggest that the omicron and Delta AY.3 were found to have relatively unstable and compact RBD structures and hampered interactions with antibodies more than wild and Delta (AY.1 and AY.2), which may lead to relatively more pathogenicity and antibody escape. In addition, we observed lower binding affinity of Omicron for human monoclonal antibodies (CR3022, B38, CB6, and P2B2F6) when compared to wild and Delta (AY.1 & AY.2). However, the binding affinity of Omicron RBD variants for CR3022, B38, and P2B2F6 antibodies is lower as compared to Delta AY.3, which might promote immune evasion and reinfection and needs further experimental investigation.

bioinformatics↗

bioRxiv2021

A Retrotranslocation Assay that Predicts Defective VCP/p97-Mediated Trafficking of a Retroviral Signal Peptide

Studies of viral replication have provided critical insights into host processes, including protein trafficking and turnover. Mouse mammary tumor virus (MMTV) is a betaretrovirus that encodes a functional 98-amino acid signal peptide (SP). MMTV SP is generated from both Rem and envelope precursor proteins by signal peptidase cleavage in the endoplasmic reticulum (ER) membrane. We previously showed that SP functions as an HIV-1 Rev-like protein that is dependent on the AAA ATPase VCP/p97 to subvert ER-associated degradation (ERAD). SP contains a nuclear/nucleolar localization sequence (NLS/NoLS) within the N-terminal 45 amino acids. To directly determine the SP regions needed for membrane extraction and trafficking, we developed a quantitative retrotranslocation assay with biotin acceptor peptide (BAP)-tagged SP proteins. Use of alanine substitution mutants of BAP-tagged MMTV SP in retrotranslocation assays revealed that mutation of amino acids 57 and 58 (M57-58) interfered with ER membrane extraction, whereas adjacent mutations did not. The M57-58 mutant also showed reduced interaction with VCP/p97 in co-immunoprecipitation experiments. Using transfection and reporter assays to measure activity of BAP-tagged proteins, both M57-58 and an adjacent mutant (M59-61) were functionally defective compared to wild-type SP. Confocal microscopy revealed defects in SP nuclear trafficking and abnormal localization of both M57-58 and M59-61. Furthermore, purified GST-tagged M57-58 and M59-61 demonstrated reduced ability to oligomerize compared to tagged wild-type SP. These experiments suggest that SP amino acids 57-58 are critical for VCP/p97 interaction and retrotranslocation, whereas residues 57-61 are critical for oligomerization and nuclear trafficking independent of the NLS/NoLS. Our results emphasize the complex host interactions with long signal peptides. IMPORTANCEEndoplasmic reticulum-associated degradation (ERAD) is a form of cellular protein quality control that is manipulated by viruses, including the betaretrovirus, mouse mammary tumor virus (MMTV). MMTV-encoded signal peptide (SP) has been shown to interact with an essential ERAD factor, VCP/p97 ATPase, to mediate its extraction from the ER membrane, also known as retrotranslocation, for RNA-binding and nuclear function. In this manuscript, we developed a quantitative retrotranslocation assay that identified an SP substitution mutant, which is defective for VCP interaction as well as nuclear trafficking, oligomer formation, and function. An adjacent SP mutant was competent for retrotranslocation and VCP interaction, but shared the other defects. Our results revealed the requirement for VCP during SP trafficking and the complex cellular pathways used by long signal peptides.

molecular biology↗

bioRxiv2021

Eelbrain: A Python toolkit for time-continuous analysis with temporal response functions

1Even though human experience unfolds continuously in time, it is not strictly linear; instead, it entails cascading processes building hierarchical cognitive structures. For instance, during speech perception, humans transform a continuously varying acoustic signal into phonemes, words, and meaning, and these levels all have distinct but interdependent temporal structures. Time-lagged regression using temporal response functions (TRFs) has recently emerged as a promising tool for disentangling electrophysiological brain responses related to such complex models of perception. Here we introduce the Eelbrain Python toolkit, which makes this kind of analysis easy and accessible. We demonstrate its use, using continuous speech as a sample paradigm, with a freely available EEG dataset of audiobook listening. A companion GitHub repository provides the complete source code for the analysis, from raw data to group level statistics. More generally, we advocate a hypothesis-driven approach in which the experimenter specifies a hierarchy of time-continuous representations that are hypothesized to have contributed to brain responses, and uses those as predictor variables for the electrophysiological signal. This is analogous to a multiple regression problem, but with the addition of a time dimension. TRF analysis decomposes the brain signal into distinct responses associated with the different predictor variables by estimating a multivariate TRF (mTRF), quantifying the influence of each predictor on brain responses as a function of time(-lags). This allows asking two questions about the predictor variables: 1) Is there a significant neural representation corresponding to this predictor variable? And if so, 2) what are the temporal characteristics of the neural response associated with it? Thus, different predictor variables can be systematically combined and evaluated to jointly model neural processing at multiple hierarchical levels. We discuss applications of this approach, including the potential for linking algorithmic/representational theories at different cognitive levels to brain responses through computational models with appropriate linking hypotheses.

neuroscience↗

bioRxiv2021

Captivity-induced behaviour and spatial learning abilities in an enigmatic, aquifer-dwelling blind eel, Rakthamichthys digressus

We investigated the impact of captive life on behaviour and learning abilities in an enigmatic, aquifer-dwelling blind eel, Rakthamichthys digressus. Of eight major behavioural traits related to exploration and activity in a novel arena, four were significantly altered by life in captivity. While the startle response upon introduction into the arena and overall swimming away from the walls increased after captivity, inactivity exhibited immediately after the startle and the reaction to an external disturbance decreased. We also observed behavioural syndromes between startle responses and horizontal wall following, and between overall activity and vertical wall following; however, these behavioural syndromes were not altered by maintenance in captivity. Interestingly, this blind-eel failed to learn a simple spatial task in a Y-maze apparatus. Captive-associated behavioural changes in R. digressus may influence their survival after reintroduction into natural habitats, and such changes must be taken into account while developing protocols for ex-situ conservation and subsequent release.

animal behavior and cognition↗

bioRxiv2021

Multi-omics profiling of Earth's biomes reveals that microbial and metabolite composition are shaped by the environment

As our understanding of the structure and diversity of the microbial world grows, interpreting its function is of critical interest for understanding and managing the many systems microbes influence. Despite advances in sequencing, lack of standardization challenges comparisons among studies that could provide insight into the structure and function of microbial communities across multiple habitats on a planetary scale. Technical variation among distinct studies without proper standardization of approaches prevents robust meta-analysis. Here, we present a multi-omics, meta-analysis of a novel, diverse set of microbial community samples collected for the Earth Microbiome Project. We include amplicon (16S, 18S, ITS) and shotgun metagenomic sequence data, and untargeted metabolomics data (liquid chromatography-tandem mass spectrometry and gas chromatography mass spectrometry), centering our description on relationships and co-occurrences of microbially-related metabolites and microbial taxa across environments. Standardized protocols and analytical methods for characterizing microbial communities, including assessment of molecular diversity using untargeted metabolomics, facilitate identification of shared microbial and metabolite features, permitting us to explore diversity at extraordinary scale. In addition to a reference database for metagenomic and metabolomic data, we provide a framework for incorporating additional studies, enabling the expansion of existing knowledge in the form of a community resource that will become more valuable with time. To provide examples of applying this database, we outline important ecological questions that can be addressed, and test the hypotheses that every microbe and metabolite is everywhere, but the environment selects. Our results show that metabolite diversity exhibits turnover and nestedness related to both microbial communities and the environment. The relative abundances of microbially-related metabolites vary and co-occur with specific microbial consortia in a habitat-specific manner, and highlight the power of certain chemistry - in particular terpenoids - in distinguishing Earths environments.

ecology↗

bioRxiv2021

Alterations in chromosome spatial compartmentalization classify prostate cancer progression

Prostate cancer aggressiveness and metastatic potential are influenced by gene expression, genomic aberrations, and cellular morphology. These processes are in turn dependent in part on the 3D structure of chromosomes, packaged inside the nucleus. Using chromosome conformation capture (Hi-C), we conducted a systematic genome architecture comparison on a cohort of cell lines that model prostate cancer progression, ranging from normal epithelium to bone metastasis. Here, we describe how chromatin compartmentalization identity (A-open vs. B-closed) changes with progression: specifically, we find that 48 gene clusters switch from the B to the A compartment, including androgen receptor, WNT5A, and CDK14. These switches could prelude transcription activation and are accompanied by changes in the structure, size, and boundaries of the topologically associating domains (TADs). Further, compartmentalization changes in chromosome 21 are exacerbated with progression and may explain, in part, the genesis of the TMPRSS2-ERG translocation: one of the main drivers of prostate cancer. These results suggest that discrete, 3D genome structure changes play a deleterious role in prostate cancer progression. SummaryThrough a systematic analysis of chromosome conformation capture in a cohort of cells that model cancer progression, San Martin et.al. find that rearrangement of the 3D genome structure in prostate cancer is a potential mechanism for disease exacerbation and that genome-wide compartment identity can classify cancer according to progression.

cancer biology↗

bioRxiv2021

OGUs enable effective, phylogeny-aware analysis of even shallow metagenome community structures

We introduce Operational Genomic Unit (OGU), a metagenome analysis strategy that directly exploits sequence alignment hits to individual reference genomes as the minimum unit for assessing the diversity of microbial communities and their relevance to environmental factors. This approach is independent from taxonomic classification, granting the possibility of maximal resolution of community composition, and organizes features into an accurate hierarchy using a phylogenomic tree. The outputs are suitable for contemporary analytical protocols for community ecology, differential abundance and supervised learning while supporting phylogenetic methods, such as UniFrac and phylofactorization, that are seldomly applied to shotgun metagenomics despite being prevalent in 16S rRNA gene amplicon studies. As demonstrated in one synthetic and two real-world case studies, the OGU method produces biologically meaningful patterns from microbiome datasets. Such patterns further remain detectable at very low metagenomic sequencing depths. Compared with taxonomic unit-based analyses implemented in currently adopted metagenomics tools, and the analysis of 16S rRNA gene amplicon sequence variants, this method shows superiority in informing biologically relevant insights, including stronger correlation with body environment and host sex on the Human Microbiome Project dataset, and more accurate prediction of human age by the gut microbiomes in the Finnish population. We provide Woltka, a bioinformatics tool to implement this method, with full integration with the QIIME 2 package and the Qiita web platform, to facilitate OGU adoption in future metagenomics studies. ImportanceShotgun metagenomics is a powerful, yet computationally challenging, technique compared to 16S rRNA gene amplicon sequencing for decoding the composition and structure of microbial communities. However, current analyses of metagenomic data are primarily based on taxonomic classification, which is limited in feature resolution compared to 16S rRNA amplicon sequence variant analysis. To solve these challenges, we introduce Operational Genomic Units (OGUs), which are the individual reference genomes derived from sequence alignment results, without further assigning them taxonomy. The OGU method advances current read-based metagenomics in two dimensions: (i) providing maximal resolution of community composition while (ii) permitting use of phylogeny-aware tools. Our analysis of real-world datasets shows several advantages over currently adopted metagenomic analysis methods and the finest-grained 16S rRNA analysis methods in predicting biological traits. We thus propose the adoption of OGU as standard practice in metagenomic studies.

bioinformatics↗

bioRxiv2021

Bioinformatics analysis of SARS-CoV-2 RBD mutant variants and insights into antibody and ACE2 receptor binding

Prevailing COVID-19 vaccines are based on the spike protein of earlier SARS-CoV-2 strain that emerged in Wuhan, China. The continuously evolving nature of SARS-CoV-2 resulting emergence of new variants raises the risk of immune absconds. During the last few months, several RBD (receptor-binding domain) variants have been reported to affect the vaccine efficacy considerably. Soon after reporting of a new double mutant variant (L452R & E484Q) in India, the country facing a deadlier second wave of infections which prompts researchers to suspects this variant to be accountable. To address the relevant concerns about this new variant affecting vaccine efficacy, we performed molecular simulation dynamics based structural analysis of spike protein of double mutant (L452R & E484Q) along with K417G variants and earlier reported RBD variants and found structural changes in RBD region after comparing with the wild type. Comparison of the binding affinity of the double mutant and earlier reported RBD variant for ACE2 (angiotensin 2 altered enzymes) receptor and CR3022 antibody with the wild-type strain revealed the lowest binding affinity of the double mutant for CR3022 among all other variants. These findings suggest that the newly emerged double mutant could significantly reduce the impact of the current vaccine which threatens the protective efficacy of current vaccine therapy.

bioinformatics↗

bioRxiv2021

SMILE: Mutual Information Learning for Integration of Single Cell Omics Data

Deep learning approaches have empowered single-cell omics data analysis in many ways, generating new insights from complex cellular systems. As there is an increasing need for single cell omics data to be integrated across sources, types, and features of data, the challenges of integrating single-cell omics data are rising. Here, we present a deep clustering algorithm that learns discriminative representation for single-cell data via maximizing mutual information, SMILE (Single-cell Mutual Information Learning). Using a unique cell-pairing design, SMILE successfully integrates multi-source single-cell transcriptome data, removing batch effects and projecting similar cell types, even from different tissues, into the same representation space. SMILE can also integrate data from two or more modalities, such as joint profiling technologies using singlecell ATAC-seq, RNA-seq, DNA methylation, Hi-C, and ChIP data. SMILE works well even when feature types are unmatched, such as genes for RNA-seq and genome wide peaks for ATAC-seq.

bioinformatics↗

bioRxiv2020

Preclinical validation of a second generation leishmanization vaccine against vector transmitted fatal visceral leishmaniasis

Visceral Leishmaniasis (VL) is fatal if untreated. There is no licensed vaccine available against human leishmaniasis. We recently demonstrated protection in mice against L. major infection using a CRISPR genome edited attenuated Leishmania major strain (LmCen-/-). Here, as a pre-clinical step, we evaluated the protective efficacy of LmCen-/- against VL induced by sand fly transmitted Leishmania donovani in hamsters. Intradermal immunization of hamsters with LmCen-/- did not develop any lesion; while still priming a pro-inflammatory immune response. When challenged with L. donovani either by intradermal needle injection or by infected sand flies, LmCen-/--immunized hamsters were protected, not showing spleen or liver pathology averting VL fatality compared to control animals. Spleen cells from LmCen-/- immunized and infected sand fly challenged hamsters produced significantly higher Th1-associated cytokines and chemokines including IFN-{gamma} and TNF-, and significantly reduced expression of the anti-inflammatory cytokines IL-10 and IL-21, compared to non-immunized challenged animals. We further developed a GLP-grade LmCen-/- which showed equal protection as laboratory-grade LmCen-/- parasites in hamsters. Importantly, GLP-grade LmCen-/- parasites also induced a proinflammatory immune response in the PBMCs isolated from healthy people living in non-endemic and endemic for VL as well as cured VL people living in endemic region. Together, this study demonstrates that the LmCen-/- parasites are safe and efficacious against VL and it is a strong candidate vaccine to be tested in a human clinical trial.

immunology↗

bioRxiv2020

Better expression profile of CD8 and CD4 gene in uterus of pregnant ewe in comparison to non-pregnant - a novel report

CD8 and CD4 T cells play a central role in the immune response to viruses and intracellular pathogens as well as functions for the maintenance of both the mother and fetus. The present study was conducted to explore the differential gene expression profile for CD8 and CD4 present in the uterus with reference to the gravid and non-gravid Garole sheep and confirmation through immuno histochemical studies. Better CD8 and CD4 gene expression was observed in the mid uterus of pregnant ewes compared to that of non-pregnant ewes, where CD8 expression was better to that of CD4. Gene expression profiling of CD8 and CD4 are reported here for the first time in sheep. CD8 and CD4 expression may be regarded as the useful factor for maintenance of pregnancy. The current observations demonstrate that during pregnancy in ewe the immune system may respond to changes in the maternal environment to maintain the size and function of the CD8 and CD4 T-cell compartment. CD8 and CD4 expression may be employed as marker for pregnancy detection in sheep, which remains always a challenge for sheep breeders.

immunology↗

bioRxiv2020

A multiscale analysis of early flower development in Arabidopsis provides an integrated view of molecular regulation and growth control

The link between gene regulation and morphogenesis of multicellular organisms is a fundamental problem in biology. We address this question in the floral meristem of Arabidopsis, which generates new tissues and organs through complex changes in growth patterns. Starting from high-resolution time-lapse images, we generated a comprehensive 4-D atlas of early flower development including cell lineage, cellular growth rates and the expression patterns of 28 regulatory genes. This information was introduced in MorphoNet, a web-based open-access platform. The application of mechanistic computational models indicated that the molecular network based on the literature only explained a minority of the expression patterns. This was substantially improved by adding single regulatory hypotheses for individual genes. We next used the integrated information to correlate growth with the combinatorial expression of multiple genes. This led us to propose a set of hypotheses for the action of individual genes in morphogenesis, not visible by simply correlating gene expression and growth. This identified the central transcription factor LEAFY as a potential regulator of heterogeneous growth, which was supported by quantifying growth patterns in a leafy mutant. By providing an integrated, multiscale view of flower development, this atlas should represent a fundamental step towards mechanistic multiscale-scale models of flower development.

developmental biology↗