Biology subjects

Mishra, S.

Publications and source records attributed to Mishra, S..

At least 73 records · Page 4Linked to original sources

bioRxiv2024

The Alzheimer's disease gene SORL1 regulates lysosome function in human microglia

AbstractThe SORL1 gene encodes the sortilin related receptor protein SORLA, a sorting receptor that regulates endo-lysosomal trafficking of various substrates. Loss of function variants in SORL1 are causative for Alzheimers disease (AD) and decreased expression of SORLA has been repeatedly observed in human AD brains. SORL1 is highly expressed in the central nervous system, including in microglia, the tissue resident immune cells of the brain. Loss of SORLA leads to enlarged lysosomes in hiPSC-derived microglia like cells (hMGLs). However, how SORLA deficiency contributes to lysosomal dysfunction in microglia and how this contributes to AD pathogenesis is not known. In this study, we show that loss of SORLA results in decreased lysosomal degradation and lysosomal enzyme activity due to altered trafficking of lysosomal enzymes in hMGLs. Phagocytic uptake of fibrillar amyloid beta 1-42 and synaptosomes is increased in SORLA deficient hMGLs, but due to reduced lysosomal degradation, these substrates aberrantly accumulate in lysosomes. An alternative mechanism of lysosome clearance, lysosomal exocytosis, is also impaired in SORL1 deficient microglia, which may contribute to an altered immune response. Overall, these data suggest that SORLA has an important role in proper trafficking of lysosomal hydrolases in hMGLs, which is critical for microglial function. This further substantiates the microglial endo-lysosomal network as a potential novel pathway through which SORL1 may increase AD risk and contribute to development of AD. Additionally, our findings may inform development of novel lysosome and microglia associated drug targets for AD.

neuroscience↗

bioRxiv2024

Dicarbonyl stress debilitates mesothelial defense against metastasizing ovarian cancer

Chronic metabolic disorders and aging result in accumulation of active dicarbonyls that glycate biomolecules rendering them dysfunctional. Although metabolic aberrations are known to be epidemiologically associated with faster cancer progression, cell biological determinants of such associations remain elusive. The formation of micro-metastases in epithelial ovarian cancer involves its colonization of visceral peritonea through clearance of mesothelia that line the coelom. In this study, we observe that cocultures of immortalized human coelomic MeT-5A mesothelia with human ovarian cancer cells OVCAR-3 and SK-OV-3 show greater infiltration by the latter when exposed to increasing concentrations of the dicarbonyl methylglyoxal (MG). Treatment with increasing concentrations of MG caused death and senescence within human and murine serosal mesothelia. Cells showed higher levels of advanced glycation end products, dysregulated occludens junction protein ZO-1, and disrupted localization of cortical filamentous actin and its regulator ezrin, indicating poor inter-cell adhesion. Time lapse imaging also showed impaired migration for MG-treated single mesothelia and for their collective monolayers. Agent-based computer modeling of coculture dynamics predicted that a combined effect of confluence and migration allows inter-adherent mesothelia to contain the spread of colonizing cancer cells, which was confirmed through coculture time lapses of cancer colonization within higher and lower mesothelial densities. We found ovarian cancer cells showed higher levels of glyoxalase-1 (GLO-1) enzyme, which catabolizes MG, suggesting how they escaped its cytotoxic effects. Consistent with this, treatment of OVCAR-3 with MG concurrently with pharmacological inhibition of GLO-1 showed greater cell death. Our results suggest dicarbonyl stress helps colonizing cancer cells overcome the resistance of natural homoeostatic barriers and its inhibition may, in supplementation with chemotherapy, stem metastasis.

cancer biology↗

bioRxiv2024

A multivariate approach to joint testing of main genetic and gene-environment interaction effects

Gene-environment (GxE) interactions crucially contribute to complex phenotypes. The statistical power of a GxE interaction study is limited mainly due to weak GxE interaction effect sizes. To utilize the individually weak GxE effects to improve the discovery of associated genetic loci, Kraft et al. [1] proposed a joint test of the main genetic and GxE effects for a univariate phenotype. We develop a testing procedure to evaluate combined genetic and GxE effects on a multivariate phenotype to enhance the power by merging pleiotropy in the main genetic and GxE effects. We base the approach on a general linear hypothesis testing framework for a multivariate regression for continuous phenotypes. We implement the generalized estimating equations (GEE) technique under the seemingly unrelated regressions (SUR) setup for binary or mixed phenotypes. We use extensive simulations to show that the test for joint multivariate genetic and GxE effects outperforms the univariate joint test of genetic and GxE effects and the test for multivariate GxE effect concerning power when there is pleiotropy. The test produces a higher power than the test for multivariate main genetic effect for a weak genetic and substantial GxE effect. For more prominent genetic effects, the latter performs better with a limited increase in power. Overall, the multivariate joint approach offers high power across diverse simulation scenarios. We apply the methods to lipid phenotypes with sleep duration as an environmental factor in the UK Biobank. The proposed approach identified six independent associated genetic loci missed by other competing methods.

genomics↗

bioRxiv2024

Cryo- EM structure of ribosome from pathogenic protozoa Entamoeba histolytica, reveals unique features of its architecture

Entamoeba histolytica, an anaerobic parasite protozoan, is the causative agent of amoebiasis, the bloody diarrhea, and liver abscesses in humans. Amoebiasis is more predominant in tropical areas with poor sanitation conditions, and it remains the fourth leading cause of death due to a protozoan infection. E. histolytica life cycle spans between an infective cyst stage and an active disease-causing trophozoite stage. We have determined cryo-EM structures of E. histolytica ribosomes, large subunit (LSU), 53S ribosome at 2.8 [A] resolution and associated, 75S ribosome at 3.3 [A] resolution, isolated from its trophozoite stage. The overall core of the ribosome is conserved. However, the periphery has evolved with Entamoeba specific unique features. The most notable features are, the presence of the rRNA triple helix near the peptide exit tunnel on LSU and the co-evolution of rRNA expansion segments and extensions in r-proteins. To the best of our knowledge, this structure reports the presence of RNA triple helix in the ribosome for the first time.

biochemistry↗

bioRxiv2024

A novel micronemal protein, Scot1, is essential for apicoplast biogenesis and liver stage development in Plasmodium berghei

Plasmodium sporozoites invade hepatocytes, transform into liver stages, and replicate into thousands of merozoites that infect erythrocytes and cause malaria. Proteins secreted from micronemes play an essential role in hepatocyte invasion, and unneeded micronemes are subsequently discarded for replication. The liver-stage parasites are potent immunogens that prevent malarial infection. Late liver stage-arresting genetically attenuated parasites (GAPs) exhibit greater protective efficacy than early GAP. However, the number of late liver-stage GAPs for generating GAPs with multiple gene deletions is limited. Here, we identified Scot1 (Sporozoite Conserved Orthologous Transcript 1), which was previously shown to be upregulated in sporozoites, and by endogenous tagging with mCherry, we demonstrated that it is expressed in the sporozoite and liver stages in micronemes. Using targeted gene deletion in Plasmodium berghei, we showed that Scot1 is essential for late liver-stage development. Scot1 KO sporozoites grew normally into liver stages but failed to initiate blood-stage infection in mice due to impaired apicoplast biogenesis and merozoite formation. Bioinformatic studies suggested that Scot1 is a metal/small molecule carrier protein. Remarkably, supplementation with metals in the culture of infected Scot1 KO cells did not rescue their phenotype. Immunization with Scot1 KO sporozoites in C57BL/6 mice confers protection against a malaria challenge via infection. These proof-of-concept studies will enable the generation of P. falciparum Scot1 mutants that could be exploited to generate GAP malaria vaccines. ImportanceMalaria parasites experience significant bottlenecks as transmitted to the mammalian host during a mosquito bite. Sporozoites invade liver cells, reproducing into thousands of merozoites, which are released after liver cell ruptures. The specific arrest of sporozoites during liver stage development acts as a powerful immunogen and provides sterile protection against sporozoite infection. GAP leading to an arrest in late liver stage development offers superior protection. Here, we report that a micronemal protein, Scot1, is essential for parasite maturation in the liver. Deletion of Scot1 resulted in impaired apicoplast biogenesis and merozoite formation. Vaccination with Scot1 KO sporozoites protects against malaria challenge. We have identified a late arresting GAP that will aid in developing new as well as safeguarding existing whole parasite vaccines.

microbiology↗

bioRxiv2024

Ca2+ binding to Esyt is required to modulate membrane contact site density in Drosophila photoreceptors

Membrane Contact Sites (MCS) between the plasma membrane (PM) and endoplasmic reticulum (ER) have been shown to regulate Ca2+ influx into animal cells. However, the mechanisms by which cells modulate ER-PM MCS density is not understood and the role of Ca2+, if any, in regulating this process is not known. We report that in Drosophila photoreceptors, MCS density is dependent on the activity of the Ca2+ permeable channels-TRP and TRPL. This regulation of MCS density by Ca2+ is mediated by extended synaptotagmin (dEsyt), a protein localised to ER-PM MCS in photoreceptors and previously shown to regulate MCS density. We find that the Ca2+ binding activity of dEsyt is required for its functional activity in vivo. dEsytCaBM, a Ca2+ non-binding mutant of dEsyt is unable to modulate MCS structure in a manner equivalent to its wild type counterpart. Further, when reconstituted in dEsyt null photoreceptors, in contrast to wild type dEsyt, dEsytCaBM is unable to rescue ER-PM MCS density and other key phenotypes. Finally, when expressed in wild type photoreceptors, dEsytCaBM phenocopies loss of dEsyt function. Taken together, our data supports a role for the Ca2+ binding activity of dEsyt in regulating the ER-PM MCS density in photoreceptors thus tuning signal transduction in response to Ca2+ influx triggered by ambient illumination. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=196 SRC="FIGDIR/small/588361v1_ufig1.gif" ALT="Figure 1"> View larger version (38K): org.highwire.dtl.DTLVardef@f8faacorg.highwire.dtl.DTLVardef@114009org.highwire.dtl.DTLVardef@8337f0org.highwire.dtl.DTLVardef@cd7c2f_HPS_FORMAT_FIGEXP M_FIG C_FIG

cell biology↗

bioRxiv2024

Conformational switch of a peptide provides a novel strategy to design peptide loaded porous organic polymer for Pyroptosis pathway mediated cancer therapy

While peptide-based drug development is now extensively explored, this strategy does have limitations, which come from their rapid excretion from the body (or shorter half-life in the body), and vulnerability to protease-mediated degradation. To overcome these limitations, here we introduce a novel strategy for the development of a peptide-based anticancer agent using the conformation switch property of a chameleon sequence stretch, which we derived from a mycobacterium secretory protein, MPT63. Then, we loaded this peptide in a new porous organic polymer (PG-DFC-POP) synthesized using phloroglucinol and acresolderivative via condensation reaction for delivering the peptide selectively to the cancer cells. Employing an ensemble and single molecule approaches, we demonstrate that this peptide undergoes a disordered to alpha-helical conformational transition, which is triggered by a low pH environment inside cancer cells. This adopted alpha-helical conformation results in the formation of proteolysis-resistant oligomers, which show efficient membrane pore-forming activity selectively for negatively charged phospholipid which is accumulated in cancer cell membrane. Our in vitro and in vivo experimental results demonstrate that the peptide-loaded nanomaterial PG-DFC-POP-PEP 1 exhibits significant cytotoxicity in cancer cells, leading to cell death through the Pyroptosis pathway that is confirmed by monitoring numerous associated events starting from lysosome membrane damage to GSDMD-induced cell membrane demolition. We believe that this novel conformational switch-based drug design strategy has great potential in endogenous environment-responsive cancer therapy and the development of future drug candidates to mitigate cancers.

biochemistry↗

bioRxiv2024

A Caenorhabditis elegans based system for high-throughput functional phenotyping of human gut microbiota

The conventional bottom-up approach to probing the human gut microbiomes link with hosts in germ-free models is hampered by considerable costs and time. To address this, our study introduces the nematode Caenorhabditis elegans as an innovative high-throughput model for exploring the gut microbiomes impact on functional phenotypes. Traditionally, C. elegans studies have used continuous feeding for bacterial administration, a method that is unsuitable for anaerobes. For the first time, we have standardized a protocol for colonizing C. elegans with human gut anaerobes. By screening a microbial culturomics library representing 70% of the gut microbiomes functional capacity, we showed successful colonization for 46% of the library. Functional phenotyping revealed that 5 of 10 strains, previously identified in vitro as inhibiting C. difficile, also inhibited in vivo. Validation of a selected strain in a germ-free mouse model confirmed colonization resistance and an immune response consistent with findings in C. elegans, underscoring the models translational potential.

microbiology↗

bioRxiv2024

A genetically-encoded nanobody sensor reveals conformational diversity in beta-arrestins orchestrated by distinct seven transmembrane receptors

Agonist-induced interaction of G protein-coupled receptors (GPCRs) with {beta}-arrestins ({beta}arrs) is a critical mechanism that regulates the spatio-temporal pattern of receptor localization and downstream signaling. While the underlying mechanism governing GPCR-{beta}arr interaction is primarily conserved and involves receptor activation and phosphorylation, there are several examples of receptor-specific fine-tuning of {beta}arr-mediated functional outcomes. Considering the key contribution of conformational plasticity of {beta}arrs in driving receptor-specific functional responses, it is important to develop and characterize novel sensors capable of reporting distinct {beta}arr conformations in cellular context. Here, we design an intrabody version of a {beta}arr-recognizing nanobody (nanobody32), referred to as intrabody32 (Ib32), in NanoLuc enzyme complementation assay format, and measure its ability to recognize {beta}arr1 and 2 in live cells upon activation of a broad set of GPCRs. We discover that Ib32 robustly recognizes activated {beta}arr1 and 2 in the plasma membrane as well as in the endosomes, and effectively mirrors {beta}arr recruitment profile upon stimulation of GPCRs. We also design an Ib32 sensor for single-photon polarization microscopy with a change in linear dichroism as readout and demonstrate its utility for monitoring {beta}arr activation upon stimulation of angiotensin receptor by its natural and biased agonists. Interestingly, when used side-by-side with a previously described sensor of {beta}arr1 conformation known as Ib30, Ib32 uncovers distinct conformational signatures imparted on {beta}arrs by different GPCRs, which is further corroborated using an orthogonal limited proteolysis assay. Taken together, our study presents Ib32 as a novel sensor to monitor {beta}arr activation and leverages it to uncover conformational diversity encoded in the GPCR-{beta}arr system with direct implications for improving the current understanding of GPCR signaling and regulatory paradigms.

biochemistry↗

bioRxiv2024

A POLR3B-variant reveals a Pol III transcriptome response dependent on La protein/SSB

RNA polymerase III (Pol III, POLR3) synthesizes tRNAs and other small non-coding RNAs. Human POLR3 pathogenic variants cause a range of developmental disorders, recapitulated in part by mouse models, yet some aspects of POLR3 deficiency have not been explored. We characterized a human POLR3B:c.1625A>G;p.(Asn542Ser) disease variant that was found to cause mis-splicing of POLR3B. Genome-edited POLR3B1625A>G HEK293 cells acquired the mis-splicing with decreases in multiple POLR3 subunits and TFIIIB, although display auto-upregulation of the Pol III termination-reinitiation subunit POLR3E. La protein was increased relative to its abundant pre-tRNA ligands which bind via their U(n)U-3-termini. Assays for cellular transcription revealed greater deficiencies for tRNA genes bearing terminators comprised of 4Ts than of [≥]5Ts. La-knockdown decreased Pol III ncRNA expression unlinked to RNA stability. Consistent with these effects, small-RNAseq showed that POLR3B1625A>Gand patient fibroblasts express more tRNA fragments (tRFs) derived from pre-tRNA 3-trailers (tRF-1) than from mature-tRFs, and higher levels of multiple miRNAs, relative to control cells. The data indicate that decreased levels of Pol III transcripts can lead to functional excess of La protein which reshapes small ncRNA profiles revealing new depth in the Pol III system. Finally, patient cell RNA analysis uncovered a strategy for tRF-1/tRF-3 as POLR3-deficiency biomarkers.

molecular biology↗

bioRxiv2024

Molecular basis of ligand promiscuity, structural mimicry, and atypical dimerization in the chemokine receptors

Selectivity of natural agonists for their cognate receptors is one of the hallmarks of the members of GPCR family, and it is crucial for the specificity of downstream signal-transduction. However, this selectivity often breaks down in the chemokine receptor subfamily, wherein a high degree of promiscuity is observed with one receptor recognizing multiple chemokines and one chemokine binding to multiple receptors. The molecular determinants of such a striking promiscuity for natural ligands in the chemokine-chemokine receptor system remain mostly elusive and represent an important knowledge gap in our current understanding. Here, we carry out a comprehensive transducer-coupling analysis, testing all known C-X-C chemokines on every C-X-C type chemokine receptor, to generate a global fingerprint of the selectivity and promiscuity encoded within this system. Taking lead from our finding, we determined cryo-EM structures of the most promiscuous receptor, CXCR2, in complex with every interacting chemokine, and deciphered the conserved molecular signatures and distinct binding modalities. While most chemokines position themselves on the receptor as a dimer, CXCL6 exhibits a monomeric binding pose induced by a previously unanticipated reorientation of its carboxyl-terminal -helix, leading to disruption of the dimer interface. Surprisingly, one of the chemokines, CXCL5, induces a ligand-swapped dimer of CXCR2, the first of its kind observed in class A GPCRs, wherein each protomer of the ligand engages its own receptor without any discernible receptor-receptor interface. These unique observations provide a possible structural mechanism for inherent functional specialization encoded in chemokines despite their convergence to a common receptor. Furthermore, we also determined cryo-EM structures of CXCR3 in complex with G-protein-biased and {beta}-arrestin-biased small molecule agonists that elucidate distinct allosteric modulations in the receptor driving their divergent transducer-coupling bias. Guided by structural analysis and experimental validation, we discover that in contrast to previously held notion, small molecule agonists of CXCR3 display robust agonism at CXCR7, an intrinsically biased, {beta}-arrestin-coupled receptor, making them first-in-class dual agonists for chemokine receptors with exclusive {beta}arr-bias at CXCR7. Taken together, our study provides molecular insights into ligand promiscuity and signaling bias at the chemokine receptors, and also demonstrates a proof of principle that naturally encoded structural mimicry can be recapitulated using synthetic pharmacophores with potential implications for developing novel therapeutics.

biochemistry↗

bioRxiv2023

Analysing the distribution of SARS-CoV-2 infections in schools: integrating model predictions with real world observations

School closures were used as strategies to mitigate transmission in the COVID-19 pandemic. Understanding the nature of SARS-CoV-2 outbreaks and the distribution of infections in classrooms could help inform targeted or precision preventive measures and outbreak management in schools, in response to future pandemics. In this work, we derive an analytical model of Probability Density Function (PDF) of SARS-CoV-2 secondary infections and compare the model with infection data from all public schools in Ontario, Canada between September-December, 2021. The model accounts for major sources of variability in airborne transmission like viral load and dose-response (i.e., the human bodys response to pathogen exposure), air change rate, room dimension, and classroom occupancy. Comparisons between reported cases and the modeled PDF demonstrated the intrinsic overdispersed nature of the real-world and modeled distributions, but uncovered deviations stemming from an assumption of homogeneous spread within a classroom. The inclusion of near-field transmission effects resolved the discrepancy with improved quantitative agreement between the data and modeled distributions. This study provides a practical tool for predicting the size of outbreaks from one index infection, in closed spaces such as schools, and could be applied to inform more focused mitigation measures. Author summaryAt the start of the COVID-19 pandemic, there was huge uncertainty around the risks of SARS-CoV-2 spread in classrooms. In the absence of early predictions surrounding classroom risks, many jurisdictions across countries closed in-person education. There is great interest in adopting a more precision approach to better inform future interventions in the context of airborne virus risks. For this purpose, we need tools that can predict the probability of the size of outbreaks within classrooms along with the impact of interventions including masks, better ventilation, and physical distancing by limiting the number of students per classroom. To this end, we have developed a robust but practical model that yields the probability of secondary infections stemming from index cases occurring within schools on a given day. During model development, the major underlying physical and biological factors that dictate the disease transmission process, both at long-range and close-range, have been accounted for. This enables our model to modify its predictions for different scenarios - and possibly allows its use beyond schools. Finally, the models predictive capability has been verified by comparing its outputs with publicly available data on SARS-CoV-2 diagnoses in Ontario public schools. To our knowledge, this is the first time an analytical model derived from mostly first principles describes real-world infection distributions, satisfactorily. The quantitative match between the theoretical prediction and real-world data offers the proposed model as a possible powerful tool for better-informed precision pandemic mitigation strategies in indoor environments like schools.

biophysics↗

bioRxiv2023

Image guided construction of a common coordinate framework for spatial transcriptome data

Spatial transcriptomics is a powerful technology for high-resolution mapping of gene expression in tissue samples, enabling a molecular level understanding of tissue architecture. The acquisition entails dissecting and profiling micron-thick tissue slices, with multiple slices often needed for a comprehensive study. However, the lack of a common coordinate framework (CCF) among slices, due to slicing and displacement variations, can hinder data analysis, making data comparison and integration challenging, and potentially compromising analysis accuracy. Here we present a deep learning algorithm STaCker that unifies the coordinates of transcriptomic slices via an image registration process. STaCker derives a composite image representation by integrating tissue image and gene expressions that are transformed to be resilient to noise and batch effects. Trained exclusively on diverse synthetic data, STaCker overcomes the training data scarcity and is applicable to any tissue type. Its performance on various benchmarking datasets shows a significant increase in spatial concordance in aligned slices, surpassing existing methods. STaCker also successfully harmonizes multiple real spatial transcriptome datasets. These results indicate that STaCker is a valuable computational tool for constructing a CCF with spatial transcriptome data.

bioinformatics↗

bioRxiv2023

reconcILS: A gene tree-species tree reconciliation algorithm that allows for incomplete lineage sorting

Reconciliation algorithms infer the evolutionary history of individual gene trees given a species tree. Many reconciliation algorithms consider only duplication and loss events (and sometimes horizontal transfer), ignoring effects of the coalescent process, including incomplete lineage sorting (ILS). Here, we present a new heuristic algorithm for carrying out reconciliation that accurately accounts for ILS by treating it as a series of nearest neighbor interchange (NNI) events. For discordant branches of the gene tree identified by last common ancestor (LCA) mapping, our algorithm recursively chooses the optimal history by comparing the cost of duplication and loss to the cost of NNI and loss. We demonstrate the accuracy of our new method, which we call reconcILS, using a new simulation engine (dupcoal) that generates gene trees produced by the interaction of duplication, loss, and ILS under the MSC-DL model. Despite being a heuristic method, reconcILS is much more accurate than models that ignore ILS, and at least as accurate or better than leading methods that can model ILS, while also able to handle much larger datasets. We demonstrate the use of reconcILS by applying it to a dataset of 23 primate genomes, highlighting its accuracy compared to standard methods in the presence of large amounts of ILS.

bioinformatics↗

bioRxiv2023

An explainable model using Graph-Wavelet for predicting biophysical properties of proteins and measuring mutational effects

Proteins hold multispectral patterns of different kinds of physicochemical features of amino acids in their structures, which can help understand proteins behavior. Here, we propose a method based on the graph-wavelet transform of signals of features of amino acids in protein residue networks derived from their structures to achieve their abstract numerical representations. Such abstract representations of protein structures hand in hand with amino-acid features can be used for different purposes, such as modelling the biophysical property of proteins. Our method outperformed graph-Fourier and convolutional neural-network-based methods in predicting the biophysical properties of proteins. Even though our method does not predict deleterious mutations, it can summarize the effect of an amino acid based on its location and neighbourhood in protein-structure using graph-wavelet to estimate its influence on the biophysical property of proteins. Such an estimate of the influence of amino-acid has the potential to explain the mechanism of the effect of deleterious non-synonymous mutations. Thus, our approach can reveal patterns of distribution of amino-acid properties in the structure of the protein in the context of a biophysical property for better classification and more insightful understanding.

bioinformatics↗

bioRxiv2023

Serum-deprivation response of ARPE-19 cells; expression patterns relevant to age-related macular degeneration.

ARPE-19 cells are derived from adult human retinal pigment epithelium (RPE). The response of these cells to the stress of serum deprivation mimics some important processes relevant to age-related macular degeneration (AMD). Here we extend the characterization of this response using RNASeq and EGSEA gene set analysis of ARPE-19 cells over nine days of serum deprivation. This experiment confirmed the up-regulation of cholesterol and lipid-associated pathways that increase cholesterol levels in these cells. The gene expression analysis also identified other pathways relevant to AMD progression. There were significant changes in extracellular matrix gene expression, notably a switch from expression of collagen IV, a key component of Bruchs membrane (part of the blood-retina barrier), to expression of a fibrosis-like collagen type I matrix. Changes in the expression profile of the extracellular matrix led to the discovery that amelotin is induced in AMD and is associated with the development of the calcium deposits seen in late-stage geographic atrophy. The transcriptional profiles of other pathways, including inflammation, complement, and coagulation, were also modified, consistent with immune response patterns seen in AMD. As previously noted, the cells resist apoptosis and autophagy but instead initiate a gene expression pattern characteristic of senescence, consistent with the maintenance of barrier function even as other aspects of RPE function are compromised. Other differentially regulated genes were identified that open new avenues for investigation. Our results suggest that ARPE-19 cells maintain significant stress responses characteristic of native RPE that are informative for AMD. As such, they provide a convenient system for discovery and for testing potential therapeutic interventions.

molecular biology↗

bioRxiv2023

Pyruvate dehydrogenase kinase expression profile is a biomarker for cancer sensitivity to dichloroacetate-mediated growth inhibition.

BackgroundCancer cells favour glycolysis and lactate production over mitochondrial metabolism despite the presence of oxygen (the Warburg effect). Increased pyruvate dehydrogenase kinase (PDK) activity contributes to this glycolytic phenotype. Dichloroacetate (DCA) is a PDK inhibitor with anti-cancer potential that inhibits all four isoforms of PDK but with differing potencies, thus expression of different isoforms may determine sensitivity to DCA. MethodsThe association of sensitivity to growth inhibition by DCA, on-target effects of DCA and expression of all four isoforms of PDKs in a range of epithelial cancer cell lines was investigated in vitro and in vivo. ResultsDCA inhibited growth of cancer cells in vivo and in vitro, reduced pyruvate dehydrogenase phosphorylation and reduced lactate production. The magnitude of the effect of DCA on growth was variable and correlated with the PDK expression profiles of the cells, with low expression of PDK3 (highest Ki for DCA) conferring the highest sensitivity towards DCA. PDK2 siRNA-knockdown inhibited growth to a similar extent to DCA, whilst PDK3 knockdown significantly increased sensitivity to DCA. ConclusionThe PDK expression profile is a potential biomarker for sensitivity to DCA, and should be considered when translating PDK inhibitors into clinical use.

cancer biology↗

bioRxiv2023

A novel glideosome-associated protein S14 coordinates sporozoite gliding motility and infectivity in mosquito and mammalian hosts

Plasmodium sporozoites are the infective forms of the malaria parasite in the vertebrate host. Gliding motility allows sporozoites to migrate and invade the salivary gland and hepatocytes. Invasion is powered by an actin-myosin motor complex linked to glideosome. However, the gliding complex and the role of several glideosome-associated proteins (GAPs) are poorly understood. In silico analysis of a novel protein, S14, which is uniquely upregulated in salivary gland sporozoites, suggested its association with glideosome-associated proteins. We confirmed S14 expression in sporozoites using real-time PCR. Further, the S14 gene was endogenously tagged with 3XHA-mCherry to study expression and localization. We found its expression and localization on the inner membrane of sporozoites. By targeted gene deletion, we demonstrate that S14 is essential for sporozoite gliding motility, salivary gland, and hepatocyte invasion. The gliding and invasion-deficient S14 KO sporozoites showed normal expression and organization of IMC and surface proteins. Using in silico and the yeast two-hybrid system, we showed the interaction of S14 with the glideosome-associated proteins GAP45 and MTIP. Together, our data show that S14 is a glideosome-associated protein and plays an essential role in sporozoite gliding motility, which is critical for the invasion of the salivary gland, hepatocyte, and malaria transmission.

microbiology↗