Biology subjects

Ghosh, A.

Publications and source records attributed to Ghosh, A..

At least 235 records · Page 13Linked to original sources

bioRxiv2020

Cognitive fluctuations surrounding sleep in daily living

It is well recognized that cognitive output fluctuates surrounding sleep. Such fluctuations are rarely investigated in subjects daily living, partially due to the inaccessibility of sleep laboratory technology and cognitive testing. Here we leverage the continuous and long-term smartphone touchscreen interaction logs to study the patterns of cognitive output surrounding sleep and contrasted these to the patterns underlying physical activity captured from wrist-worn actigraphy. According to spectral density analysis, both cognitive and physical activity was dominated by diurnal ([~]24 h) and infra-radian ([~]7 days) rhythms. However, these rhythms differed in a domain-specific manner. The proxy measures of cognitive performance - tapping speed, unlocking speed, and app locating speed - contained lower-powered diurnal rhythm than physical activity. Still, the amount of smartphone usage showed the strongest diurnal rhythm - even when compared to the ambient luminescence levels experienced according to actigraphy. Interestingly, the cognitive rhythms were not in sync with physical activity, as cognitive measures peaked later in the day and on weekdays rather than weekends. The difference between cognitive and physical activity became vivid during bedtime and subjects routinely interacted with their smartphones during the actigraphy labelled sleep period. The cognitive measures in this period were worse in comparison to the hour before or after sleep. Therefore, smartphones can seamlessly capture the dynamic fluctuations in cognitive output including during spontaneous awakenings. We conclude that the rhythms underlying cognitive activity in the real world are distinct from physical activity and this discord may be a hallmark of modern human behaviour.

animal behavior and cognition↗

bioRxiv2020

Striatal dopamine synthesis capacity reflects smartphone social activity

Striatal dopamine has been implicated in social behavior across humans, rodents, and non-human primates in artificial laboratory settings with highly-practiced tasks and fixed reward contingencies. Whether striatal dopamine drives naturalistic, spontaneous social behavior remains unclear. Here, we leverage day-to-day logs of unconstrained smartphone behavior and establish a novel link between smartphone social activity and individual differences in striatal dopamine synthesis capacity using [18F]-DOPA PET in (N=22) healthy adult humans. We find a strong relationship such that a higher proportion of social app interactions correlates with lower dopamine synthesis capacity in the bi-lateral putamen. Permutation tests and penalized regressions provide evidence that this link between dopamine synthesis capacity and social versus non-social smartphone taps is specific. These observations provide a key empirical grounding for current speculations about dopamines role in digital social behavior.

neuroscience↗

bioRxiv2020

Global Spread of SARS-CoV-2 Subtype with Spike Protein Mutation D614G is Shaped by Human Genomic Variations that Regulate Expression of TMPRSS2 and MX1 Genes

COVID-19 pandemic is a major human tragedy. Worldwide, SARS-CoV-2 has already infected over 3 million and has killed about 230,000 people. SARS-CoV-2 originated in China and, within three months, has evolved to an additional 10 subtypes. One particular subtype with a non-silent (Aspartate to Glycine) mutation at 614th position of the Spike protein (D614G) rapidly outcompeted other pre-existing subtypes, including the ancestral. We assessed that D614G mutation generates an additional serine protease (Elastase) cleavage site near the S1-S2 junction of the Spike protein. We also identified that a single nucleotide deletion (delC) at a known variant site (rs35074065) in a cis-eQTL of TMPRSS2, is extremely rare in East Asians but is common in Europeans and North Americans. The delC allele facilitates entry of the 614G subtype into host cells, thus accelerating the spread of 614G subtype in Europe and North America where the delC allele is common. The delC allele at the cis-eQTL locus rs35074065 of TMPRSS2 leads to overexpression of both TMPRSS2 and a nearby gene MX1. The cis-eQTL site, rs35074065 overlaps with a transcription factor binding site of an activator (IRF1) and a repressor (IRF2). IRF1 activator can bind to variant delC allele, but IRF2 repressor fails to bind. Thus, in an individual carrying the delC allele, there is only activation, but no repression. On viral entry, IRF1 mediated upregulation of MX1 leads to neutrophil infiltration and processing of 614G mutated Spike protein by neutrophil Elastase. The simultaneous processing of 614G spike protein by TMPRSS2 and Elastase serine proteases facilitates the entry of the 614G subtype into host cells. Thus, SARS-CoV-2, particularly the 614G subtype, has spread more easily and with higher frequency to Europe and North America where the delC allele regulating expression of TMPRSS2 and MX1 host proteins is common, but not to East Asia where this allele is rare.

genomics↗

bioRxiv2020

How did SARS-CoV-19 spread in India from Italy, Iran and China? Genetic surveillance of early cases and virus demography

SARS-CoV-19 after emerging from Wuhan, drastically devastated all sectors of human life by crushing down the global economy and increased psychological burden on public, government, and healthcare professionals. We manifested by analyzing 35 early coronavirus cases of India, that virus introduction in India, occurred from Italy, Iran and China and population demography apparently revealed a rapid population expansion after the outbreak with a present steady growth. We depicted nucleotide substitutions in structural genes, drove for the adaptive selection and plead for sequencing more genomes to facilitate identification of new emerged mutants, genetic evolution and disease transmission caused by coronavirus.

genomics↗

bioRxiv2020

Decoding molecular markers and transcriptional circuitry of naive and primed states of human pluripotency

Pluripotent stem cells (PSCs) have been observed to occur in two distinct states -- naive and primed. Both naive and primed state PSCs can give rise to tissues of all the three germ layers in vitro but differ in their potential to generate germline chimera in vivo. Understanding the molecular mechanisms that govern these two states of pluripotency in human can open up a plethora of opportunities for studying early embryonic development and in biomedical applications. In this work, we use weighted gene co-expression network (WGCN) approach to identify the key molecular makers and their interactions that define the two distinct pluripotency states. Signed-hybrid WGCN was reconstructed from transcriptomic data (RNA-seq) of naive and primed state pluripotent samples. Our analysis revealed two sets of genes that are involved in establishment and maintenance of naive (4791 genes) and primed (5066 genes) states. The naive state genes were found to be enriched for biological processes and pathways related to metabolic processes while primed state genes were associated with system development. Further, we identified the top 10% genes by intra-modular connectivity as hubs and the hub transcription factors for each group, thus providing a three-tier list of genes associated with naive and primed states of pluripotency in human. HIGHLIGHTSO_LIWeighted gene co-expression network analysis (WGCNA) identified 4791 and 5066 genes to be involved in naive and primed states of human pluripotency respectively. C_LIO_LIFunctional and pathway enrichment analysis revealed the naive genes were mostly related to metabolic processes and primed genes to system development. C_LIO_LIThe top 10% genes based on intra-modular connectivity from each group were defined as hubs. C_LIO_LIIdentified 52 and 33 transcription factors among the naive and primed module hubs respectively. C_LIO_LIThe transcription factors might play a switch on-off mechanism in induction of the two pluripotent states. C_LI

bioinformatics↗

bioRxiv2020

Locus coeruleus patterns differentially modulate learning and valence in rat via the ventral tegmental area and basolateral amygdala respectively

The locus coeruleus (LC), the main source of forebrain norepinephrine, produces phasic and tonic firing patterns that are theorized to have distinct functional consequences. However, how different firing modes affect learning and valence coding of sensory information are unknown. Here bilateral optogenetic activation of rat LC neurons using 10-Hz phasic trains of either 300 msec or 10 sec accelerates acquisition of a food-rewarded similar odor discrimination, but not a dissimilar odor discrimination, consistent with LC-supported enhanced pattern separation and plasticity. Similar odor discrimination learning is impaired by noradrenergic blockade in the piriform cortex (PC). However, here 10-Hz LC phasic light-mediated learning facilitation is prevented by a dopaminergic antagonist in the PC, or by ventral tegmental area (VTA) silencing with lidocaine, suggesting an LC-VTA-PC dopamine circuitry mediates 10-Hz phasic learning facilitation. Tonic stimulation at 10 Hz did not alter odor discrimination acquisition, and was less effective in activating VTA DA neurons. For valence encoding, tonic stimulation at 25 Hz induced freezing, anxiety and conditioned odor aversion, while 10-Hz phasic stimulation produced an odor preference consistent with positive valence. Noradrenergic blockade in the basolateral amygdala (BLA) prevented conditioned odor preference and aversion induced by 10-Hz phasic and 25-Hz tonic light respectively. CTB retro-labeling showed relatively larger engagement of nucleus accumbens projecting neurons over central amygdala projecting neurons in the BLA with 10-Hz LC phasic activation, compared to 25-Hz tonic. These outcomes argue that LC pauses, as well as LC firing frequencies, differentially influence both target networks and behaviour.

neuroscience↗

bioRxiv2020

NFATc acts as a non-canonical phenotypic stability factor for a hybrid epithelial/mesenchymal phenotype

Metastasis remains the cause of over 90% of cancer-related deaths. Cells undergoing metastasis use phenotypic plasticity to adapt to their changing environmental conditions and avoid therapy and immune response. Reversible transitions between epithelial and mesenchymal phenotypes - Epithelial-Mesenchymal Transition (EMT) and its reverse Mesenchymal-Epithelial Transition (MET) - form a key axis of phenotypic plasticity during metastasis and therapy resistance. Recent studies have shown that the cells undergoing EMT/MET can attain one or more hybrid epithelial/mesenchymal (E/M) phenotypes, the process of which is termed as partial EMT/MET. Cells in hybrid E/M phenotype(s) can be more aggressive than those in either epithelial or mesenchymal state. Thus, it is crucial to identify the factors and regulatory networks enabling such hybrid E/M phenotypes. Here, employing an integrated computational-experimental approach, we show that the transcription factor NFATc can inhibit the process of complete EMT, thus stabilizing the hybrid E/M phenotype. It increases the range of parameters enabling the existence of a hybrid E/M phenotype, thus behaving as a phenotypic stability factor (PSF). However, unlike previously identified PSFs, it does not increase the mean residence time of the cells in hybrid E/M phenotypes, as shown by stochastic simulations; rather it enables the co-existence of epithelial, mesenchymal and hybrid E/M phenotypes and transitions among them. Clinical data suggests the effect of NFATc on patient survival in a tissue-specific or context-dependent manner. Together, our results indicate that NFATc behaves as a non-canonical phenotypic stability factor for a hybrid E/M phenotype.

cancer biology↗

bioRxiv2020

Exploration of endo-xylanase from novel strain of Bacillus velezensis AG20 isolated from the cave of Meghalaya

Cave sets the example of extreme ecological niche and habitat for diversified microorganisms. Present study involved in the isolation of endoxylanase producing novel strain Bacillus velezensis AG20 from the Krem Phyllut cave, Meghalaya, India. Culture dependent studies, molecular phylogentics, RNA secondary folding pattern based on 16S rDNA substantiated the identity of this novel strain. Bacillus velezensis AG20 revealed the superbug quality having resistance against various class of broad-spectrum antibiotics. Bacillus velezensis AG20 revealed biofilm formation over the cell surface in FESEM. Highest cell biomass and xylanase production supported in TB medium, further purified partially to 5.3 fold with 21% yield. Molecular weight of the purified xylanase found to be 45 kDa. Enzyme kinetics and pattern of hydrolysis revealed the evidence for the selection of linear birchwood xylan with Vmax = 21.0 {+/-} 3.0 U/ml, Km = 1.25 mg/ml, Kcat = 1.75/s at optimum pH 7 and temperature 50{degrees}C also found significant statistically in Taguchis orthogonal design. Conversely, ruled out any exoacting activity against synthetic pNP-xylopyranoside substrate. Endo-xylanase isolated from Bacillus velezensis AG20 was moderately thermostable over temperatures 50 and 60{degrees}C. Time dependent hydrolysis of agro-waste sugar cane bagasse depicted the production of xylooligosaccharides (XOS) predominantly xylobiose, xylotriose and xylotetrose. Purified mixed XOS hold their prebiotic potential by promoting the growth of probiotics Bifidobacterium and Lactobacillus as well as high stability (~90%) against systemic fluids. Mixed XOS (300 g/ml) displayed anti-proliferation activities by reducing the growth of HT-29 and Caco-2 cells significantly 90% and 75%, respectively, after 48 h. IMPORTANCEExtremophiles dwelling inside the caves have laden with the extraordinary capabilities of bioconversion by nature. The pristine ecological niche inside the cave, absence of proper light and air, supports the livelihood of novel microorganisms. In India, Meghalaya is hoisting longest caves in the East Khasi Hills, providing conducive environment for novel bacterial strains. With the prime objective of isolating novel bacterial strains that produce extracellular xylanase our studies have been carried out. Considering the present industrial demand for nutraceutical, prebiotics, anti-proliferating agents and biofuels by the conversion of lignocellulosic biomass (LCB), novel enzymes are required. Xylanases from bacterial origin play a significant role in conversion of LCB into oligosaccharides. Therefore, exploration and characterization of xylanase producing novel isolate from cave may pave the new arena for the production of prebiotic and anti-inflammatory oligosaccharides from agro-waste.

microbiology↗

bioRxiv2020

Biological function polarity prediction of missense variants using machine learning

Functional interpretation is crucial when facing on average 20,000 missense variants per human exome, as the great majority are not associated with any underlying disease. In silico bioinformatics tools can predict the deleteriousness of variants or assess their functional impact by assigning scores, but they cannot predict whether the variant in question results in gain or loss of function at the protein level. Here, we show that machine learning can effectively predict this biological function polarity of missense variants. The new method adapts weighted gradient boosting machine approach on a set of damaging variants (1,288 loss of function and 218 gain of function variants) as annotated by the tools SIFT, PolyPhen2 and CADD. Area under the ROC curve of 0.85 illustrates high discriminative power of the classifier. Predictive performance of the classifier remains consistent against an independent set of damaging variants as highlighted by the area under the ROC curve of 0.83. This new approach may help to guide biological experiments on the clinical relevance of damaging genetic variants. Author summaryMissense variant occurs when a single genetic alteration in DNA takes place and as a result a new amino acid is translated into the protein. This amino acid change can inactivate the existing protein function causing loss-of-function or produce a new function causing gain-of-function. Therefore, it is very important to interpret these functional consequences of missense variants as they often turn out to be disease causing. Each individuals genome sequence has thousands of missense variants, out of which very few are actually associated with any underlying disease. Various computational tools have been developed to predict whether missense variants are damaging or not, but none of them can actually predict whether the damaging missense variants cause gain-of-function or loss-of-function. We have developed a new ensemble classifier to predict this biological function polarity at the protein level. The classifier combines the prediction scores of three existing bioinformatics tools and applies machine learning to make effective predictions. We have validated our classifier against an independent data set to show its high predictive power and robustness. The predictions made by our machine learning tool can be used as indicators of biological function polarity, but with further evidence on pathogenicity.

bioinformatics↗

bioRxiv2020

The Role of Oxygen Intake and Liver Enzyme on The Dynamics of Damaged Hepatocytes}: \\ Implications to Ischaemic Liver Injury via A Mathematical Model.

Ischaemic Hepatitis (IH) or Hypoxic Hepatitis (HH) also known as centrilobular liver cell necrosis is an acute liver injury characterized by a rapid increase in serum aminotransferase. The liver injury typically results from another underlying medical conditions like cardiac failure, respiratory failure and septic shock in which the liver becomes damaged due to deprivation of either blood or oxygen. IH is a potentially lethal condition which is often preventable if diagnosed properly. Unfortunately, mechanism that causes IH are often not well understood, making it difficult to diagnose or accurately quantify the patterns of related biomakers. In most cases, currently the only way to determine a case of IH (i.e., to diagnose it) is to rule out all other possible conditions for other liver injuries. A better understanding of the livers response to IH is necessary to aid in its diagnosis, measurement and improve outcomes. The goal of this study, is to identify mechanisms that can alter a few associated biomarkers for reducing density of damaged hepatocytes, and thus reduce chances of IH. To this end, we develop a mathematical model capturing dynamics of hepatocytes in the liver through the rise and fall of associated liver enzymes aspartate transaminase (AST), alanine transaminase (ALT) and lactate dehydrogenase (LDH) related to condition of IH. The model analysis provides a novel approach to predict the level of biomarkers given variations in the systemic oxygen in the body. Using IH patient data in US, novel model parameters are described and then estimated for the first time to capture real time dynamics of hepatocytes in the presence and absence of IH condition. Different scenarios of patient conditions were also analyzed and validated using empirical information. This study and its results may allow physicians to estimate the extent of liver damage in a IH patient based on their enzyme levels and receive faster treatment on real time basis.

cell biology↗

bioRxiv2020

Prognostic significance of SOCS1 and SOCS3 tumor suppressors in hepatocellular carcinoma and its correlation to key oncogenic signaling pathways

Suppressor of cytokine signaling (SOCS) proteins SOCS1 and SOCS3 are considered tumor suppressors in liver hepatocellular carcinoma (LIHC). To gain insight into the underlying molecular mechanisms, the expression of SOCS1/ SOCS3 was evaluated in The Cancer Genome Atlas LIHC dataset along with key oncogenic signaling pathway genes. SOCS1 expression was not significantly reduced in HCC yet higher expression predicted favorable prognosis, whereas SOCS3 lacked predictive potential despite lower expression. Only a small proportion of the cell cycle, receptor tyrosine kinase, growth factor and RAS-RAF-MEK-MAPK signaling genes negatively correlated with SOCS1 or SOCS3, of which even fewer showed elevated expression in HCC and predicted survival. However, many PI3K-AKT-MTOR pathway genes showed mutual exclusivity with SOCS1/SOCS3 and displayed independent predictive ability. Among genes that negatively correlated with SOCS1/SOCS3, CDK2, MLST8, AURKA, MAP3K4 and RPTOR showed corresponding modulations in the livers of mice lacking Socs1 or Socs3 during liver regeneration and in experimental HCC, and in Hepa1-6 murine HCC cells overexpressing SOCS1/SOCS3. However, Cox proportional hazards model identified CXCL8, DAB2 and PIK3R1 as highly predictive in combination with SOCS1 or SOCS3. These data suggest that developing prognostic biomarkers and precision treatment strategies based on SOCS1/SOCS3 expression need careful testing in different patient cohorts.

cancer biology↗

bioRxiv2020

A Tug of War Between Condensate Phases in a Minimal Macromolecular System

Membraneless organelles formed via liquid-liquid phase separation (LLPS) contain a multitude of macromolecular species. A few of these species drive LLPS while most serve as regulators. The LLPS of SH35 (S) and PRM5 (P), two oppositely charged protein constructs, was promoted by a polyanion heparin (H) but suppressed by a cationic protein lysozyme (L). Here, using these four components alone, we demonstrate complex phase behaviors associated with membraneless organelles and uncover the underlying physical rules. The S:P, S:L, and P:H binaries form droplets, but the H:L binary forms precipitates, therefore setting off a tug of water between different phases within the S:P:H:L quaternary. We observe dissolution of precipitates upon compositional change, transformation from precipitates to droplet-like condensates over time, and segregation of S:L-rich and P:H-rich foci inside droplet-like condensates. A minimal macromolecular system can thus recapitulate membraneless organelles in essential ways and provide crucial physical understanding.

biophysics↗

bioRxiv2019

Alzheimers disease-related dysregulation of protein synthesis causes key pathological features with ageing

Alzheimers disease (AD) is characterised by A{beta} and tau pathology as well as synaptic degeneration. Recently, it was suggested that the development of these key disease features may at least in part be due to increased protein synthesis that is regulated by fragile X mental retardation protein (FMRP) and its binding partner CYFIP2. Using an unbiased screen, we show that exposure of primary neurons to A{beta} increases FMRP-regulated protein synthesis and involves a reduction of CYFIP2 levels. Modelling this CYFIP2 reduction in mice, we find A{beta} accumulation, development of pre-tangle tau pathology, gliosis, loss of synapses, and deficits in memory formation with ageing. We conclude that reducing endogenous CYFIP2 expression is sufficient to cause some key features of AD in mice. We therefore propose a central role for CYFIP2 in AD as a modulator of protein synthesis, highlighting a novel direction for therapeutic targeting.

neuroscience↗

bioRxiv2019

Dimerization of human drebrin-like protein governs its biological activity

Drebrin-like protein (DBNL) is a multidomain F-actin binding protein, which also interacts with other molecules within different intracellular pathways. Here, we present quantitative measurements on size and conformation of human DBNL. Using dual focus fluorescence correlation spectroscopy, we determined the hydrodynamic radius of DBNL monomer. Native gel electrophoresis and dual color fluorescence cross-correlation spectroscopy show that both endogenous and recombinant DBNL exist as dimer under physiological conditions. We demonstrate that C-terminal truncations of DBNL downstream of the coiled-coil domain result in its oligomerization at nanomolar concentration. In contrast, the ADF-H domain alone is a monomer, which displays a concentration-dependent self-assembly. In vivo FLIM-FRET imaging shows that the presence of only actin-binding domains is not sufficient for DBNL to localize properly at actin filament inside the cell. In summary, our work provides a detailed insight on structure-function relationship of human drebrin-like protein.

biophysics↗

bioRxiv2019

Estimating brain age from structural MRI and MEG data: Insights from dimensionality reduction techniques

Brain age prediction studies aim at reliably estimating the difference between the chronological age of an individual and their predicted age based on neuroimaging data, which has been proposed as an informative measure of disease and cognitive decline. As most previous studies relied exclusively on magnetic resonance imaging (MRI) data, we hereby investigate whether combining structural MRI with functional magnetoencephalography (MEG) information improves age prediction using a large cohort of healthy subjects (N=613, age 18-88 yrs) from the Cam-CAN repository. To this end, we examined the performance of dimensionality reduction and multivariate associative techniques, namely Principal Component Analysis (PCA) and Canonical Correlation Analysis (CCA), to tackle the high dimensionality of neuroimaging data. Using MEG features (mean absolute error (MAE) of 9.60 yrs) yielded worse performance when compared to using MRI features (MAE of 5.33 yrs), but a stacking model combining both feature sets improved age prediction performance (MAE of 4.88 yrs). Furthermore, we found that PCA resulted in inferior performance, whereas CCA in conjunction with Gaussian process regression models yielded the best prediction performance. Notably, CCA allowed us to visualize the features that significantly contributed to brain age prediction. We found that MRI features from subcortical structures were more reliable age predictors than cortical features, and that spectral MEG measures were more reliable than connectivity metrics. Our results provide an insight into the underlying processes that are reflective of brain aging, yielding promise for the identification of reliable biomarkers of neurodegenerative diseases that emerge later during the lifespan.

neuroscience↗

bioRxiv2019

An allosteric hot-spot in the tandem-SH2 domain of ZAP-70 regulates T-cell signaling

T-cell receptor (TCR) signaling is initiated by recruiting ZAP-70 to the cytosolic part of TCR. ZAP-70, a non-receptor tyrosine kinase, is composed of an N-terminal tandem SH2 (tSH2) domain connected to the C-terminal kinase domain. The ZAP-70 is recruited to the membrane through binding of tSH2 domain and the doubly-phosphorylated ITAM motifs of CD3 chains in the TCR complex. Our results show that the tSH2 domain undergoes a biphasic structural transition while binding to the doubly-phosphorylated ITAM-{zeta}1 peptide. The C-terminal SH2 domain binds first to the phosphotyrosine residue of ITAM peptide to form an encounter complex leading to subsequent binding of second phosphotyrosine residue to the N-SH2 domain. We decipher a network of non-covalent interactions that allosterically couple the two SH2 domains during binding to doubly-phosphorylated ITAMs. Mutation in the allosteric network residues, for example, W165C, uncouples the formation of encounter complex to the subsequent ITAM binding thus explaining the altered recruitment of ZAP-70 to the plasma membrane causing autoimmune arthritis in mice. The proposed mechanism of allosteric coupling is unique to ZAP-70, which is fundamentally different from Syk, a close homolog of ZAP-70 expressed in B-cells. SignificanceT-cell and B-cell signaling is initiated by the same family of non-receptor tyrosine kinases, ZAP-70 and Syk, respectively. ZAP-70 and Syk share homologous sequence and similar structural architecture, yet the two kinases differ in their mode of ligand recognition. ZAP-70 binds cooperatively to its ligand, whereas Syk binds uncooperatively. Spontaneous mutation (W165C) in the regulatory module of ZAP-70 impairs T-cell signaling causes autoimmune arthritis in SKG mice, the mechanism of which is unknown. We showed that ZAP-70 regulatory module undergoes a biphasic structural transition while binding to its ligand, which is fundamentally different from Syk. We presented a molecular mechanism of cooperativity in ZAP-70 regulatory module that explains altered ligand binding by ZAP-70 mutant found in SKG mice.

biochemistry↗

bioRxiv2019

Atypical Protein Kinase C iota (PKC{lambda}/{iota}) Ensures Mammalian Development by Establishing the Maternal-Fetal Exchange Interface

In utero mammalian development relies on the establishment of the maternal-fetal exchange interface, which ensures transportation of nutrients and gases between the mother and the fetus. This exchange interface is established via development of multinucleated syncytiotrophoblast cells (SynTs) during placentation. In mouse, SynTs develop via differentiation of the trophoblast progenitor cells (TSPCs) of the placenta primordium and in human, SynTs are developed via differentiation of villous cytotrophoblast (CTB) progenitors. Despite the critical need in pregnancy progression, conserved signaling mechanisms that ensure SynT development are poorly understood. Herein, we show that Atypical Protein Kinase C iota (PKC{lambda}/I) plays an essential role in establishing the SynT differentiation program in trophoblast progenitors. Loss of PKC{lambda}/I in the mouse TSPCs abrogates SynT development leading to embryonic death at ~E9.0. We also show that PKC{lambda}/I-mediated priming of trophoblast progenitors for SynT differentiation is a conserved event during human placentation. PKC{lambda}/I is selectively expressed in the first-trimester CTBs of a developing human placenta. Furthermore, loss of PKC{lambda}/I in CTB-derived human trophoblast stem cells (Human TSCs) impairs their SynT differentiation potential both in vitro and after transplantation in immunocompromised mice. Our mechanistic analyses indicate that PKC{lambda}/I signaling maintains expression of GCM1, GATA2, and PPAR{gamma}, which are key transcription factors to instigate SynT differentiation programs in both mouse and human trophoblast progenitors. Our study uncovers a conserved molecular mechanism, in which PKC{lambda}/I signaling regulates establishment of the maternal-fetal exchange surface by promoting trophoblast progenitor to SynT transition during placentation.

developmental biology↗

bioRxiv2019

Trophoblast paracrine signaling regulates placental hematoendothelial niche

The placenta acts as a major organ for hematopoiesis. It is believed that placental hematopoietic stem and progenitor cells (HSPCs) migrate to the fetal liver to ensure optimum hematopoiesis in the developing embryo. The labyrinth vasculature in a mid-gestation mouse placenta provides a niche for the definitive hematopoietic stem cell (HSC) generation and expansion. It has been proposed that these processes are regulated by a host of paracrine factors secreted by trophoblast giant cells (TGCs) at the maternal-fetal interface. However, the molecular mechanism by which the TGCs regulate the hematoendothelial niche in a developing placenta is yet to be defined. Using a TGC-specific Gata2 and Gata3 double knockout mouse model, we show that the loss of GATA2 and GATA3 at the TGC layer leads to fetal growth retardation and embryonic death due to disruptions in the delicate hematopoietic-angiogenic balance in the developing placenta. Using single-cell RNA-Seq analyses, we also show that the loss of GATA factors in the TGCs results in the loss of HSC population within the placental labyrinth and is associated with defective placental angiogenesis. Interestingly, we also found that this TGC-specific GATA factor-loss leads to impaired differentiation and distribution of trophoblast progenitor cells. Our study helps to define the GATA-dependent non-autonomous signaling mechanisms of the primary parietal trophoblast giant cells by which it regulates the delicate hematopoietic-angiogenic balance in the developing placenta.

developmental biology↗