Biology subjects

Acharya, G.

Publications and source records attributed to Acharya, G..

16 recordsLinked to original sources

bioRxiv2026

Novel polymeric fluoropyrimidine CF10 demonstrates superior therapeutic index and survival advantage in patient-derived models of 5-fluorouracil-refractory colorectal cancer

BackgroundFluoropyrimidines, specifically 5-fluorouracil (5-FU), remain the cornerstone of colorectal cancer (CRC) therapy. However, intrinsic and acquired resistance, alongside dose-limiting systemic toxicities, often result in treatment failure and disease relapse. There is a pressing clinical need for next-generation fluoropyrimidines that can retain the antitumor activity in 5-FU-refractory CRC models while maintaining a favorable safety profile. MethodsWe evaluated the antitumor efficacy of CF10, a novel polymeric fluoropyrimidine designed for the sustained delivery of FdUMP, against equimolar 5-FU. We utilized a diverse panel of six patient-derived CRC organoid (PDO) models to assess 3D growth inhibition under both normoxic ([~]20% O2) and physioxic (5% O2) conditions. Mechanisms of action were investigated via {gamma}H2AX signaling (DNA damage), Annexin V/PI flow cytometry (death kinetics), and ALDEFLUOR assays (stem-like populations). Functional suppression of metastasis-associated phenotypes was evaluated using 3D Matrigel invasion assays. Finally, the therapeutic index and overall survival were validated in vivo using two independent patient-cell-derived xenograft (PCDX) models (TX-CC-199 and TX-CC-201). ResultsCF10 demonstrated significantly greater suppression of organoid growth compared to equimolar 5-FU across all patient-derived lines, regardless of morphological heterogeneity or oxygen tension. In 3D invasion assays, CF10 achieved superior anti-invasive activity even at a 10-fold lower molar dose than 5-FU. This functional advantage was mirrored by a marked depletion of the ALDH-high stem-like subpopulation, which was largely recalcitrant to 5-FU. Mechanistically, CF10 induced intensified replication stress, DNA damage and repair signaling ({gamma}H2AX, Top1cc/pRPA32, FANCD2), and pushed the CRC to irreversible/terminal, PI-positive death states. In vivo, CF10 treatment resulted in profound tumor growth inhibition and a robust survival advantage in two patient cell-derived xenograft (PCDX) models (Log-rank P<0.01) without inducing systemic weight loss or noticeable toxicity. ConclusionsBy integrating 3D patient-derived modeling with in vivo validation, we demonstrate that CF10 effectively overcomes the biological and pharmacological limitations of 5-FU. CF10 targets the aggressive, invasive, and stem-like subpopulations of CRC that drive clinical relapses. These findings provide a compelling translational rationale for the clinical development of CF10 as a superior alternative to standard fluoropyrimidines in both treatment-naive and refractory CRC. Significance StatementDespite the foundational role of 5-fluorouracil (5-FU) in colorectal cancer (CRC) therapy, resistance and systemic toxicity remain major barriers to curative outcomes. This study identifies CF10, a novel polymeric fluoropyrimidine, as a superior alternative that overcomes 5-FU resistance in biologically diverse patient-derived organoids and xenograft models. Crucially, CF10 demonstrates a unique capacity to suppress the invasive, aldehyde dehydrogenase (ALDH)-high stem-like subpopulations that likely survive standard chemotherapy (5-FU) by maintaining efficacy under physiological oxygen levels and providing a significant survival advantage in vivo with improved tolerability. CF10 represents a promising translational candidate for the treatment of both treatment-naive and refractory CRC.

cancer biology↗

bioRxiv2026

Passive neuromodulation: an energy-driven mechanism for closed-loop suppression of epileptic seizure

For decades, electrical neuromodulation has been used as a therapeutic mechanism to disrupt and desynchronize pathological neural activity in various neurological disorders. Despite notable progress, however, patient outcomes remain highly variable, particularly in medically intractable epilepsy where surgery still provides the greatest chance of seizure freedom. Here we propose passive neuromodulation (PNM) as a radical alternative to conventional neurostimulation, whereby analogue feedback is used to drain energy from an epileptic circuit and thus suppress the initiation or spread of electrographic seizures. We provide pilot evidence on the efficacy and robustness of PNM using two computational models of epileptic dynamics: a detailed biophysical network model of dentate gyrus, and the Epileptor neural mass model of seizure dynamics. Despite the vast differences between these models, our results show the robust ability of PNM to suppress seizures in both models. We further demonstrate the efficacy and robustness of responsive PNM, whereby brief (50ms) windows of PNM are triggered by a simultaneously-running seizure detection algorithm, as well as the safe and tunable nature of PNM, where more robust seizure suppression can be achieved by parametrically titrating the amount of power drained from the tissue, without inducing any seizures even if applied interictally. Overall, our results provide strong evidence on the promise of PNM for the closed-loop control of epileptic seizures and other neurological disorders where damping pathological network activity can restore healthy dynamics.

neuroscience↗

bioRxiv2026

Targeted Epigenetic Modulation Outperforms Nuclease- and Deaminase-Based Editing for Durable Pcsk9 Silencing in a Clinically Relevant Delivery System

Inhibition of proprotein convertase subtilisin/kexin type 9 (PCSK9) lowers low-density lipoprotein cholesterol, a major risk factor for cardiovascular disease. Although several gene therapy strategies targeting Pcsk9 have been developed, direct comparisons across modalities are limited. To address this, we systematically evaluated cytosine base editing, nuclease-based CRISPR-Cas9, and epigenetic gene editing for Pcsk9 suppression. We first engineered a cytosine base editor to introduce a premature stop codon, then optimized and characterized an epigenetic editor, and finally delivered all modalities as mRNA formulated in Arcturus lipid nanoparticles (LUNAR(R)) into wild-type mice, benchmarking them against conventional CRISPR-Cas9 and GalNAc-siRNA. Remarkably, epigenetic editing achieved the most efficient and sustained repression of PCSK9, maintaining low protein levels throughout the entire 30-day study period. By comparison, cytosine base editing reduced PCSK9 with minimal double-stranded DNA breaks and off-target effects, but editing precision requires further improvement, while GalNAc-siRNA produced only transient suppression, limiting its suitability for a one-time therapeutic approach. Collectively, these findings highlight the superior durability and efficacy of epigenetic gene editing and provide proof-of-concept for its combination with LUNAR(R) delivery as a promising strategy for long-lasting hepatic-targeted therapy.

molecular biology↗

bioRxiv2025

Multiscale predictive modeling robustly improves the accuracy of pseudo-prospective seizure forecasting in drug-resistant epilepsy

Extensive research over the past two decades has focused on identifying a preictal period in scalp as well as intracranial EEG (iEEG). This has led to a plethora of seizure prediction and forecasting algorithms which have reached only moderate success on curated and pre-segmented EEG datasets (accuracy/AUC {gtrsim} 0.8). Furthermore, when tested on their ability to pseudo-prospectively predict seizures from continuous EEG recordings, all existing algorithms suffer from low sensitivity (large false negatives), high time in warning (large false positives), or both. In this study we provide pilot evidence that predictive modeling of the dynamics of iEEG features (biomarkers), seizure risk, or both at the scale of tens of minutes can significantly improve the pseudo-prospective accuracy of almost any state-of-the-art seizure forecasting model. In contrast to the bulk of prior research that has focused on designing better features and classifiers, we start from off-the-shelf features and classifiers and shift the focus to learning how iEEG features (classifier input) and seizure risk (classifier output) evolve over time. Using iEEG from n = 5 patients undergoing presurgical evaluation at the Hospital of the University of Pennsylvania and six state-of-the-art baseline models, we first demonstrate that a wide array of iEEG features are highly predictable over time, with over 99% and 35% of studied features, respectively, having R2 > 0 for 10-second- and 10-minute-ahead prediction (mean R2 of 0.85 and 0.2). Furthermore, in almost all patients and baseline models, we observe a strong correlation between feature predictability (with some features remaining predictable up to 30 minutes) and classification-based feature importance. As a result, we subsequently demonstrate that adding an autoregressive model that predicts iEEG features on 12 {+/-} 4 minutes into the future is almost universally beneficial, with a mean improvement of 28% in terms of area under pseudo-prospective sensitivity-time in warning curve (PP-AUC). Addition of the second autoregressive predictive model at the level of seizure risk further improved accuracy, with a total mean improvement of 51% in PP-AUC. Our results provide pioneering evidence for the long-term predictability of seizure-relevant iEEG features and the vast utility of time series predictive modeling for improving seizure forecasting using continuous intracranial EEG.

neuroscience↗

bioRxiv2025

Acute high-dose irradiation of human primary ovarian cells reveals a shift in transcriptomics profile and impairment in cell-cell adhesion

STUDY QUESTIONHow do human cortical (cPOCs) and medullary (mPOCs) primary ovarian cells respond to acute X-ray exposure? SUMMARY ANSWERAcute high-dose X-ray exposure causes a shift in cPOCs and mPOCs transcriptomic profiles and impairs significantly their cell-cell adhesion ability. WHAT IS KNOWN ALREADYRadiotherapy is a leading cancer treatment, due to its effectiveness in targeting malignant cells. However, it can also affect healthy cells, potentially causing organ dysfunction, among which ovaries. When targeted radiotherapy is not feasible, fertility preservation is recommended to avoid premature ovarian insufficiency. In addition, the effects of irradiation on ovarian somatic cells remain poorly understood. STUDY DESIGN, SIZE, DURATIONOvarian tissue was obtained from patients undergoing gender-affirming surgery at Karolinska University Hospital Huddinge, Sweden. The ovarian tissue was separated into cortex and medulla, then individually dissociated into single-cell suspensions using mechanical and enzymatic methods. Monolayer cultures from cPOCs and mPOCs were exposed to a single dose of 10 Gy X-ray irradiation or left unexposed as paired controls. Following irradiation, the cells were cultured at various time-points for further molecular and morphological evaluation. PARTICIPANTS/MATERIALS, SETTING, METHODSOvarian tissue from 8 patients (age 23-36 years) was used. Dissociated cPOCs and mPOCs were cultured to 80% confluence and irradiated with 10 Gy (1.33 Gy/min), with non-irradiated controls. Cellular ATP and mitochondrial activity were assessed, followed by immunofluorescence staining for canonical irradiation-induced effects in cells: DNA damage, apoptosis and cell cycle progression. Bulk RNA-sequencing was performed on controls and irradiated samples. Libraries were prepared using the Illumina Stranded mRNA Prep Ligation protocol and sequenced on Illumina NovaSeq6000 platform. Genes were considered to be differentially expressed under the cut-off of false discovery rate (FDR) < 0.05. Subsequently, affected biological pathway was predicted using all expressed genes ranked by log2 fold change again hallmark gene sets. To further investigate the potential upstream regulators, transcription factor enrichment analysis were performed based on DEGs. To assess changes at protein level, we mapped the proteomic profile using liquid chromatography-tandem mass spectrometry. Peptides were considered to be differentially expressed (DEPs) under the cut-off of p-value < 0.01. Finally, we measured the ability of cPOCs and mPOCs to form 3D aggregates after seeding irradiated and non-irradiated cells on Biosilk scaffolds. MAIN RESULTS AND THE ROLE OF CHANCEFollowing irradiation, ATP levels and mitochondrial activity in cPOCs and mPOCs were comparable to controls, indicating minimal irradiation impact on cell viability and proliferation. Immunofluorescence analysis confirmed the modulation of canonical pathways, such as DNA damage, apoptosis and cell cycle in both cPOCs and mPOCs. Transcriptomic analysis showed that cPOCs and mPOCs at 1 h post-irradiation clustered together with the related 1 h control. However, a shift in transcriptomic profile was observed after 4 h and even more after 24 h post-irradiation in both cPOCs and mPOCs. Gene set enrichment analysis (GSEA) indicated upregulation of the p53 pathway at 4 h and 24 h post-irradiation, alongside downregulation of MYC targets, E2F targets, the G2/M checkpoint and mTORC1 pathway. Gene pattern analysis showed irradiation-dependent trends related to extracellular matrix (ECM) organisation, p53-mediated apoptotic mechanisms and chromosome segregation during the 24 h period following irradiation. Additionally, transcription factor enrichment analysis based on DEGs suggested p53 and MYC as potential upstream regulators. On a proteomic level, DEPs associated with ECM organisation and cytoskeleton formation were detected at 4 and 24 h post-irradiation. Finally, X-ray exposure hindered the cell-cell adhesion ability of both cPOCs and mPOCs, leading to impaired formation of Silk-Ovarioids. LARGE SCALE DATAThe RNA sequencing count matrix is deposited in Gene Expression Omnibus (GEO) with accession number GSE291604. The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD061796. The code used for the analysis can be found at https://github.com/tialiv/X-Ovary. LIMITATIONS, REASONS FOR CAUTIONThe ovarian tissue was obtained from gender-affirming surgery patients who received androgen treatment before removal. Even though unlikely, this hormonal treatment might influence ovarian environment and alter cellular response to irradiation. Additionally, in this study the impact of X-ray exposure was assessed on a monolayer cell model, thus limiting the extrapolation power of our results to ovary in vivo. Lastly, the impact of irradiation was focused on the somatic cell populations that are essential for ovarian function. Further studies are needed to investigate the effects of X-ray exposure on ovarian follicles and their function. WIDER IMPLICATIONS OF THE FINDINGSUnderstanding the roles of MYC, p53 and cell adhesion factors in response to irradiation could guide the development of future ovarian protective strategies. These findings lay the foundation for further studies on ovarian tissue protection and fertility preservation in cancer patients. STUDY FUNDING/COMPETING INTEREST(S)This work was funded by the European Unions HORIZON 2020 research and innovation programme (MATER) under the Marie Skodowska-Curie Actions (grant agreement No: 813707), the Estonian Research Council (grants PRG1076 and PSG608), the Orion Research Foundation sr personal grant, the Research grant from the Center for Innovative Medicine (CIMED) and the Karolinska Institutet Consolidator Grant.

cell biology↗

bioRxiv2025

Comprehensive 16S rRNA gene sequencing and meta-transcriptomic analyses in female reproductive tract microbiota: Two molecular profiles with different messages

In recent years, high-throughput sequencing technologies have revolutionised reproductive microbiome research. Our understanding of the endometrial microbiome is primarily based on DNA-based 16S rRNA gene profiling, but DNA detection does not imply alive microbe presence. While this method is cost-effective and widely used, it has notable limitations, including the underestimation of microbial diversity, abundance, and functionality, as well as limited species-level resolution. Meta-transcriptomic analysis, an RNA-based approach, addresses these shortcomings by capturing functional transcripts that are actively expressed in living microbes. This study aims to characterize the endometrial microbiota through a dual approach, by integrating 16S rRNA gene sequencing and meta-transcriptomic analyses. By simultaneously analysing microbial composition and gene expression within the female reproductive tract samples, we seek to provide a more comprehensive understanding of its microbiota and their functional potential. A total of 49 women, aged 27-42 years, were enrolled in the study. Vaginal swabs, endometrial brushings, and endometrial biopsy samples were collected from each participant during the mid-secretory menstrual cycle phase, 6-9 days post luteinizing hormone surge. Our findings suggest that in low-microbial-biomass environments like the endometrium, the correlation between 16S rRNA gene sequencing and meta-transcriptomics is relatively weak. This highlights the limitations of microbial analysis of low-microbial-biomass samples. Alternatively, it suggests that microbial functions and genome activity are tissue-specific and dependent on the host tissue environment. Moreover, RNA-based analysis provides higher resolution in detecting certain pathogens, even within the endometrium. In conclusion, our study underscores the need to integrate genomic and transcriptomic data in microbiota studies to better elucidate critical and health-related microbiota-host interactions.

genomics↗

bioRxiv2024

Silk-Ovarioids: Establishment and characterization of human ovarian primary cells 3D-model system

In vitro models that mimic ovaries are crucial for elucidating the biological mechanisms underlying follicle activation and growth. Three-dimensional (3D) systems are particularly relevant because they can replicate the heterogeneity and cell-cell communication between different ovarian cell types. However, complex models using human ovarian primary cells have not yet been established. In this study, we developed and characterized long-term cultured 3D models of primary ovarian somatic cells isolated from adult tissues, using Biosilk as a scaffold. We successfully established both ovarian cortex- and medulla-derived 3D systems, termed Silk-Ovarioids. The presence of key ovarian somatic cell types - including granulosa, stromal, endothelial, and perivascular cells - was confirmed by transcriptomics, proteomics, and immunostaining. Notably, Silk-Ovarioids exhibited the formation of a pro-angiogenic hypoxic core, as evidenced by the development of vessel-like structures after six weeks of culture. The Silk-Ovarioids demonstrated low intra-batch variability and long-term culture stability, underscoring their potential as a robust step towards creating a bioengineered, patient-specific artificial ovary.

cell biology↗

bioRxiv2023

Predictive Modeling of Evoked Intracranial EEG Response to Medial Temporal Lobe Stimulation in Patients with Epilepsy

Despite promising advancements, closed-loop neurostimulation for drug-resistant epilepsy (DRE) still relies on manual tuning and produces variable outcomes, while automated predictable algorithms remain an aspiration. As a fundamental step towards addressing this gap, here we study predictive dynamical models of human intracranial EEG (iEEG) response under parametrically rich neurostimulation. Using data from n = 13 DRE patients, we find that stimulation-triggered switched-linear models with [~]300ms of causal historical dependence best explain evoked iEEG dynamics. These models are highly consistent across different stimulation amplitudes and frequencies, allowing for learning a generalizable model from abundant STIM OFF and limited STIM ON data. Further, evoked iEEG in nearly all subjects exhibited a distance-dependent pattern, whereby stimulation directly impacts the actuation site and nearby regions ([lsim] 20mm), affects medium-distance regions (20 [~] 100mm) through network interactions, and hardly reaches more distal areas ({gtrsim} 100mm). Peak network interaction occurs at 60[~]80mm from the stimulation site. Due to their predictive accuracy and mechanistic interpretability, these models hold significant potential for model-based seizure forecasting and closed-loop neurostimulation design.

neuroscience↗

bioRxiv2023

Super-resolution histology of paraffin-embedded samples via photonic chip-based microscopy

Fluorescence-based super-resolution optical microscopy (SRM) techniques allow the visualization of biological structures beyond the diffraction limit of conventional microscopes. Despite its successful adoption in cell biology, the integration of SRM into the field of histology has been deferred due to several obstacles. These include limited imaging throughput, high cost, and the need for complex sample preparation. Additionally, the refractive index heterogeneity and high labeling density of commonly available formalin-fixed paraffin-embedded (FFPE) tissue samples pose major challenges to applying existing super-resolution microscopy methods. Here, we demonstrate that photonic chip-based microscopy alleviates several of these challenges and opens avenues for super-resolution imaging of FFPE tissue sections. By illuminating samples through a high refractive-index waveguide material, the photonic chip-based platform enables ultra-thin optical sectioning via evanescent field excitation, which reduces signal scattering and enhances both the signal-to-noise ratio and the contrast. Furthermore, the photonic chip provides decoupled illumination and collection light paths, allowing for total internal reflection fluorescence (TIRF) imaging over large and scalable fields of view. By exploiting the spatiotemporal signal emission via MUSICAL, a fluorescence fluctuation-based super-resolution microscopy (FF-SRM) algorithm, we demonstrate the versatility of this novel microscopy method in achieving superior contrast super-resolution images of diverse FFPE tissue sections derived from human colon, prostate, and placenta. The photonic chip is compatible with routine histological workflows and allows multimodal analysis such as correlative light-electron microscopy (CLEM), offering a promising tool for the adoption of super-resolution imaging of FFPE sections in both research and clinical settings.

pathology↗

bioRxiv2022

Multi-omics analysis of paracetamol exposure identifies dysregulated genes involved in neurotoxicity and neuronal differentiation of human embryonic stem cells

Prenatal paracetamol exposure has been associated with neurodevelopmental outcomes in childhood. Pharmacoepigenetic studies show differences in cord blood DNA methylation between paracetamol exposed and unexposed neonates. However, causal implications and impact of long-term prenatal long-term paracetamol exposure on brain development remain unclear. Using a multi-omics approach, we investigated the effects of paracetamol on a model of early human brain development. We exposed human embryonic stem cells undergoing in vitro neuronal differentiation to daily media changes with paracetamol concentrations corresponding to maternal therapeutic doses. Single-cell RNA-seq and ATAC-seq integration identified paracetamol-induced chromatin-opening changes linked to gene expression. Differentially methylated and/or expressed genes were involved in signalling, neurotransmission, and cell fate-determination trajectories. Some genes involved in neuronal injury and development-specific pathways, such as KCNE3, overlapped with differentially methylated genes previously identified in cord blood associated with prenatal paracetamol exposure. Our data suggest that paracetamol may play a causal role in impaired neurodevelopment. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=191 HEIGHT=200 SRC="FIGDIR/small/519620v2_ufig1.gif" ALT="Figure 1"> View larger version (53K): org.highwire.dtl.DTLVardef@e1a75forg.highwire.dtl.DTLVardef@b36a1forg.highwire.dtl.DTLVardef@fc25e4org.highwire.dtl.DTLVardef@1bb1c8_HPS_FORMAT_FIGEXP M_FIG C_FIG

cell biology↗

bioRxiv2022

An FcRn-targeted mucosal vaccine against SARS-CoV-2 infection and transmission

SARS-CoV-2 and its variants cause COVID-19, which is primarily transmitted through droplets and airborne aerosols. To prevent viral infection and reduce viral spread, vaccine strategies must elicit protective immunity in the airways. FcRn transfers IgG across epithelial barriers; we explore FcRn-mediated respiratory delivery of SARS-CoV-2 spike (S). A monomeric IgG Fc was fused to a stabilized S protein; the resulting S-Fc bound to S-specific antibodies (Ab) and FcRn. A significant increase in Ab responses was observed following the intranasal immunization of mice with S-Fc formulated in CpG as compared to the immunization with S alone or PBS. Furthermore, we intranasally immunize adult or aged mice and hamsters with S-Fc. A significant reduction of virus replication in nasal turbinate, lung, and brain was observed following nasal challenges with SARS-CoV-2, including Delta and Omicron variants. Intranasal immunization also significantly reduced viral transmission between immunized and naive hamsters. Protection was mediated by nasal IgA, serum-neutralizing Abs, tissue-resident memory T cells, and bone marrow S-specific plasma cells. Hence FcRn delivers an S-Fc antigen effectively into the airway and induces protection against SARS-CoV-2 infection and transmission. Based on these findings, FcRn-targeted non-invasive respiratory immunizations are superior strategies for preventing highly contagious respiratory viruses from spreading.

immunology↗

bioRxiv2022

A multi-omics approach to visualize early neuronal differentiation in 4D

Neuronal differentiation of pluripotent stem cells is an established method to study physiology, disease and medication safety. However, the sequence of events in human neuronal differentiation and the ability of in vitro models to recapitulate early brain development are poorly understood. We developed a protocol optimized for the study of early human brain development and neuropharmacological applications. We comprehensively characterized gene expression and epigenetic profiles at four timepoints, as the cells differentiate from embryonic stem cells towards a heterogenous population of progenitors, immature and mature neurons bearing telencephalic signatures. A multi-omics roadmap of neuronal differentiation, combined with searchable interactive gene analysis tools, allows for extensive exploration of early neuronal development and the effect of medications. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=178 SRC="FIGDIR/small/478732v1_ufig1.gif" ALT="Figure 1"> View larger version (55K): org.highwire.dtl.DTLVardef@163539forg.highwire.dtl.DTLVardef@72c09org.highwire.dtl.DTLVardef@dc04eforg.highwire.dtl.DTLVardef@c821d2_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIMulti-omics charting a new neuronal differentiation protocol for human ES cells C_LIO_LISingle-cell analyses reveals marker genes during neuronal differentiation C_LIO_LIIdentified transcriptional waves similar to early human brain development C_LIO_LISearchable tools to visualize single-cell gene expression and chromatin state C_LI In BriefWe have developed a novel protocol for human embryonic stem cells to study neural induction and early neuronal differentiation. Multi-omics analyses uncovered cell populations, genes and transcriptional waves defining cell fate commitment. We comprehensively describe epigenetic landscapes and gene expression and provide searchable analysis tools for exploration of the data.

cell biology↗

bioRxiv2022

Robust and reproducible neuronal differentiation of human embryonic stem cells for neurotoxicology

Neuronal differentiation from pluripotent cells is commonly used to recapitulate events in early brain development. Neuronal precursors and developing neurons cultured in vivo, rely on attachment, density and cell-to-cell communication, and cell-passaging steps should be minimised to avert disruption of network cross-connectivity. This is crucial both for viability and maturation, and the former also applies to human embryonic stem cells (hESCs). Neuronal differentiation protocols from hESCs for neurotoxicology assessment studies should therefore provide standardized cell density requirements, and optimised coating matrix conditions. The effect of drug treatments may be masked by compound instability and degradation in cell culture medium but performing daily media changes can circumvent these issues. Here, we describe a robust neuronal differentiation protocol using dual SMAD/WNT signalling inhibitors LDN193189, SB431542 and XAV939 (LSX) for neural induction of hESCs, followed by self-patterning and cell maturation stages, for the generation of ventral telencephalic progenitors and neurons. We provide critical information on the optimized cell culture parameters and standardized methods of stage-specific validation. Using cell counts, immunofluorescence, qRT-PCR, and a proof of principle treatment with valproic acid to showcase issues with drug-induced cell toxicity, we facilitate reproducibility of the protocol. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=193 SRC="FIGDIR/small/477818v1_ufig1.gif" ALT="Figure 1"> View larger version (43K): org.highwire.dtl.DTLVardef@19f0f89org.highwire.dtl.DTLVardef@1b4feaaorg.highwire.dtl.DTLVardef@1bb832borg.highwire.dtl.DTLVardef@1a07efd_HPS_FORMAT_FIGEXP M_FIG C_FIG

cell biology↗

bioRxiv2021

Photonic chip-based multimodal super-resolution microscopy for histopathological assessment of cryopreserved tissue sections

1.Histopathological assessment involves the identification of anatomical variations in tissues that are associated with diseases. While diffraction-limited optical microscopes assist in the diagnosis of a wide variety of pathologies, their resolving capabilities are insufficient to visualize some anomalies at subcellular level. Although a novel set of super-resolution optical microscopy techniques can fulfill the resolution demands in such cases, the system complexity, high operating cost, lack of multimodality, and low-throughput imaging of these methods limit their wide adoption in clinical settings. In this study, we interrogate the photonic chip as an attractive high-throughput super-resolution microscopy platform for histopathology. Using cryopreserved ultrathin tissue sections of human placenta, mouse kidney, and zebrafish eye retina prepared by the Tokuyasu method, we validate the photonic chip as a multi-modal imaging tool for histo-anatomical analysis. We demonstrate that photonic-chip platform can deliver multi-modal imaging capabilities such as total internal reflection fluorescence microscopy, intensity fluctuation-based optical nanoscopy, single-molecule localization microscopy, and correlative light-electron microscopy. Our results demonstrate that the photonic chip-based super-resolution microscopy platform has the potential to deliver high-throughput multimodal histopathological analysis of cryopreserved tissue samples.

pathology↗

bioRxiv2020

AGORA2: Large scale reconstruction of the microbiome highlights wide-spread drug-metabolising capacities.

The human microbiome influences the efficacy and safety of a wide variety of commonly prescribed drugs, yet comprehensive systems-level approaches to interrogate drug-microbiome interactions are lacking. Here, we present a computational resource of human microbial genome-scale reconstructions, deemed AGORA2, which accounts for 7,206 strains, includes microbial drug degradation and biotransformation, and was extensively curated based on comparative genomics and literature searches. AGORA2 serves as a knowledge base for the human microbiome and as a metabolic modelling resource. We demonstrate the latter by mechanistically modelling microbial drug metabolism capabilities in single strains and pairwise models. Moreover, we predict the individual-specific drug conversion potential in a cohort of 616 colorectal cancer patients and controls. This analysis reveals that some drug activation capabilities are present in only a subset of individuals, moreover, drug conversion potential correlate with clinical parameters. Thus, AGORA2 paves the way towards personalised, predictive analysis of host-drug-microbiome interactions.

systems biology↗

bioRxiv2020

Visualizing ultrastructural details of placental tissue with super-resolution structured illumination microscopy

Super-resolution fluorescence microscopy is a widely employed technique in cell biology research, yet remains relatively unexplored in the field of histo-pathology. Here, we describe the sample preparation steps and acquisition parameters necessary to obtain fluorescent multicolor super-resolution structured illumination microscopy (SIM) images of both formalin-fixed paraffin-embedded and cryo-preserved placental tissue sections. We compare super-resolved images of chorionic villi against diffraction-limited deconvolution microscopy and demonstrate the significant contrast and resolution enhancement attainable with SIM. We show that SIM resolves ultrastructural details such as the syncytiotrophoblasts microvilli brush border, which up until now has been only resolvable by electron microscopy.

pathology↗