Biology subjects

Jain, A.

Publications and source records attributed to Jain, A..

At least 181 records · Page 10Linked to original sources

bioRxiv2021

Identification of Discriminative Gene-level and Protein-level Features Associated with Gain-of-Function and Loss-of-Function Mutations

Identifying whether a given genetic mutation results in a gene product with increased (gain-of-function; GOF) or diminished (loss-of-function; LOF) activity is an important step toward understanding disease mechanisms as they may result in markedly different clinical phenotypes. Here, we generated the first extensive database of all currently known germline GOF and LOF pathogenic mutations by employing natural language processing (NLP) on the available abstracts in the Human Gene Mutation Database. We then investigated various gene- and protein-level features of GOF and LOF mutations by applying machine learning and statistical analyses to identify discriminative features. We found that GOF mutations were enriched in essential genes, autosomal dominant inheritance, protein binding and interaction domains, whereas LOF mutations were enriched in singleton genes, protein-truncating variants, and protein core regions. We developed a user-friendly web-based interface that enables the extraction of selected subsets from the GOF/LOF database by a comprehensive set of annotated features, and downloading up-to-date versions (https://itanlab.shinyapps.io/goflof/). These results could ultimately improve our understanding of how mutations affect gene/protein function thereby guiding future treatment options.

genetics↗

bioRxiv2020

Intra-host variability in global SARS-CoV-2 genomes as signatures of RNA editing: implications in viral and host response outcomes

During the course of the COVID-19 pandemic, large-scale genome sequencing of SARS-CoV-2 has been useful in tracking its spread and in identifying Variants Of Concern (VOC). Besides, viral and host factors could contribute to variability within a host that can be captured in next-generation sequencing reads as intra-host Single Nucleotide Variations (iSNVs). Analysing 1, 347 samples collected till June 2020, we recorded 18, 146 iSNV sites throughout the SARS-CoV-2 genome. Both, mutations in RdRp as well as APOBEC and ADAR mediated RNA editing seem to contribute to the differential prevalence of iSNVs in hosts. Noteworthy, 41% of all unique iSNVs were reported as SNVs by 30th September 2020 in samples submitted to GISAID, which increased to [~]80% by 30th June 2021. Following this, analysis of another set of 1, 798 samples sequenced in India between November 2020 and May 2021 revealed that majority of the Delta (B.1.617.2) and Kappa (B.1.617.1) variations appeared as iSNVs before getting fixed in the population. We also observe hyper-editing events at functionally critical residues in Spike protein that could alter the antigenicity and may contribute to immune escape. Thus, tracking and functional annotation of iSNVs in ongoing genome surveillance programs could be important for early identification of potential variants of concern and actionable interventions. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=177 SRC="FIGDIR/small/417519v3_ufig1.gif" ALT="Figure 1"> View larger version (41K): org.highwire.dtl.DTLVardef@12b6ac2org.highwire.dtl.DTLVardef@16df897org.highwire.dtl.DTLVardef@dbbec2org.highwire.dtl.DTLVardef@c8de14_HPS_FORMAT_FIGEXP M_FIG C_FIG

genomics↗

bioRxiv2020

Host autophagy mediates organ wasting and nutrient mobilization for tumor growth

During tumor growth - when nutrient and anabolic demands are high - autophagy supports tumor metabolism and growth through lysosomal organelle turnover and nutrient recycling1. Ras-driven tumors additionally invoke non-autonomous autophagy in the microenvironment to support tumor growth, in part through transfer of amino acids2-4. Here we uncover a third critical role of autophagy in mediating systemic organ wasting and nutrient mobilization for tumor growth using a well-characterized malignant tumor model in Drosophila melanogaster. Micro-computed X-ray tomography and metabolic profiling reveal that RasV12; scrib-/- tumors grow 10-fold in volume, while systemic organ wasting unfolds with progressive muscle atrophy, loss of body mass, -motility, -feeding and eventually death. Tissue wasting is found to be mediated by autophagy and results in host mobilization of amino acids and sugars into circulation. Natural abundance Carbon 13 tracing demonstrates that tumor biomass is increasingly derived from host tissues as a nutrient source as wasting progresses. We conclude that host autophagy mediates organ wasting and nutrient mobilization that is utilized for tumor growth.

cell biology↗

bioRxiv2020

AttentiveDist: Protein Inter-Residue Distance Prediction Using Deep Learning with Attention on Quadruple Multiple Sequence Alignments

Protein 3D structure prediction has advanced significantly in recent years due to improving contact prediction accuracy. This improvement has been largely due to deep learning approaches that predict inter-residue contacts and, more recently, distances using multiple sequence alignments (MSAs). In this work we present AttentiveDist, a novel approach that uses different MSAs generated with different E-values in a single model to increase the co-evolutionary information provided to the model. To determine the importance of each MSAs feature at the inter-residue level, we added an attention layer to the deep neural network. The model is trained in a multi-task fashion to also predict backbone and orientation angles further improving the inter-residue distance prediction. We show that AttentiveDist outperforms the top methods for contact prediction in the CASP13 structure prediction competition. To aid in structure modeling we also developed two new deep learning-based sidechain center distance and peptide-bond nitrogen-oxygen distance prediction models. Together these led to a 12% increase in TM-score from the best server method in CASP13 for structure prediction.

bioinformatics↗

bioRxiv2020

Heterotrimeric kinesin-2 motor subunit, KLP68D, localises Drosophila odour receptor coreceptor in the distal domain of the olfactory cilia

Ciliary localisation of the odour receptor coreceptor (Orco) is essential for insect olfaction. Here, we show that in the Drosophila antenna Orco enters the bipartite cilia expressed on the olfactory sensory neurons in two discrete, one-hour intervals after the adult eclosion. Genetic analyses suggest that the heterotrimeric kinesin-2 is essential for Orco transfer from the base into the cilium. Using in vitro pulldown assay, we show that Orco binds to the C-terminal tail domain of KLP68D, the {beta}-subunit of kinesin-2. Reduced Orco enrichment decreases electrophysiological response to odours and loss of olfactory behaviour. Finally, we show that kinesin-2 function is necessary to compact Orco to an approximately four-micron stretch at the distal portion of the ciliary outer-segment bearing singlet microtubule filaments. Altogether, these results highlight an independent, tissue-specific regulation of Orco entry at specific developmental stages and its localisation to a ciliary subdomain by kinesin-2. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=199 SRC="FIGDIR/small/395905v1_ufig1.gif" ALT="Figure 1"> View larger version (69K): org.highwire.dtl.DTLVardef@177d376org.highwire.dtl.DTLVardef@1dc14d6org.highwire.dtl.DTLVardef@1dc2d21org.highwire.dtl.DTLVardef@16e90c_HPS_FORMAT_FIGEXP M_FIG C_FIG Author SummaryJana, Jain, Dutta et al., show that the odour receptor coreceptor only enters the cilia expressed on olfactory sensory neurons at specified developmental stages requiring heterotrimeric kinesin-2. The motor also helps to localise the coreceptor in a compact, environment-exposed domain at the ciliary outer-segment. HighlightsO_LIOdorant receptor coreceptor (Orco) selectively enters the olfactory cilia. C_LIO_LIOrco localises in a specific domain at the distal segment of the olfactory cilium. C_LIO_LIOrco/ORx binds to the C-terminal tail domain of the kinesin-2{beta} motor subunit. C_LIO_LIOrco entry across the transition zone and its positioning require Kinesin-2. C_LI

cell biology↗

bioRxiv2020

Increased Colonic Expression of ACE2 Associates with Poor Prognosis in Crohn's disease

Background and AimsThe host receptor for SARS-CoV-2, angiotensin-converting enzyme 2 (ACE2), is highly expressed in small intestine. Our aim was to study colonic ACE2 expression in Crohns disease (CD) and non-inflammatory bowel disease (non-IBD) controls. We hypothesized that the colonic expression levels of ACE2 impacts CD course. MethodsWe examined the expression of colon ACE2 using RNA-seq and quantitative (q) RT-PCR from 69 adult CD and 14 NIBD control patients. In a subset of this cohort we validated ACE2 protein expression and localization in formalin-fixed, paraffin-embedded matched colon and ileal tissues using immunohistochemistry. The impact of increased ACE2 expression in CD for the risk of surgery was evaluated by a multivariate regression analysis and a Kaplan-Meier estimator. To provide critical support for the generality of our findings, we analyzed previously published RNA-seq data from two large independent cohorts of CD patients. ResultsColonic ACE2 expression was significantly higher in a subset of adult CD patients (ACE2-high CD). IHC in a sampling of ACE2-high CD patients confirmed high ACE2 protein expression in the colon and ileum compared to ACE2-low CD and NIBD patients. Notably, we found that ACE2-high CD patients are significantly more likely to undergo surgery within 5 years of diagnosis, with a Cox regression analysis finding that high ACE2 levels is an independent risk factor (OR 2.18; 95%CI, 1.05-4.55; p=0.037). ConclusionIncreased intestinal expression of ACE2 is associated with deteriorated clinical outcomes in CD patients. These data point to the need for molecular stratification that may impact CD disease-related outcomes.

genomics↗

bioRxiv2020

Interactive design of GPU-accelerated Image Data Flow Graphs and cross-platform deployment using multi-lingual code generation

Modern life science relies heavily on fluorescent microscopy and subsequent quantitative bio-image analysis. The current rise of graphics processing units (GPUs) in the context of image processing enables batch processing large amounts of image data at unprecedented speed. In order to facilitate adoption of this technology in daily practice, we present an expert system based on the GPU-accelerated image processing library CLIJ: The CLIJ-assistant keeps track of which operations formed an image and suggests subsequent operations. It enables new ways of interaction with image data and image processing operations because its underlying GPU-accelerated image data flow graphs (IDFGs) allow changes to parameters of early processing steps and instantaneous visualization of their final results. Operations, their parameters and connections in the IDFG are stored at any point in time enabling the CLIJ-assistant to offer an undo-function for virtually unlimited rewinding parameter changes. Furthermore, to improve reproducibility of image data analysis workflows and interoperability with established image analysis platforms, the CLIJ-assistant can generate code from IDFGs in programming languages such as ImageJ Macro, Java, Jython, JavaScipt, Groovy, Python and C++ for later use in ImageJ, Fiji, Icy, Matlab, QuPath, Jupyter Notebooks and Napari. We demonstrate the CLIJ-assistant for processing image data in multiple scenarios to highlight its general applicability. The CLIJ-assistant is open source and available online: https://clij.github.io/assistant/

bioinformatics↗

bioRxiv2020

Modeling PPRV pathogenesis in mice to assess the contribution of innate cells and anti-viral T cells

We demonstrate a rapid induction of type I IFN response in PPRV stimulated cells and the susceptibility of mice, genetically ablated of interferon response, to PPRV infection. Following PPRV infection, IFNR KO mice gradually reduced their body weights and succumbed to the infection within 10 days. While the infecting inoculum size did not alter the outcome of infection, the nature of the induced disease was qualitatively different. Immunopathological lesions were characterized by the expansion and infiltration of innate immune cells distinctly evident at the lower infecting dose of PPRV infection. The replicating virus particles as well as the viral antigens were abundant in most of the critical organs of PPRV infected IFNR KO mice. Neutrophils and macrophages transported the replicating virus to central nervous system and contributed to pathology while the NK cells and T cells were protective against the virus. Using an array of fluorescently labeled H-2Kb tetramers PPRV specific CD8+ T cells responses were identified and measured in the infected as well as the peptide immunized mice. Our study therefore established and employed a laboratory animal model for investigating PPRV pathogenesis and the contribution of virus specific CD8+ T cells during the virus infection to pave the way for elucidating protective or pathological roles of immune cells during PPRV infection. ImportanceWe developed a laboratory animal model for investigating the pathogenesis and immunity induced by PPRV. IFNR KO animals succumbed to the infection irrespective of the dose and the route of infection. Neutrophils and macrophages served as the Trojan horse and helped transport the virus to CNS to cause encephalitis while the NK cells and CD8+ T cells provided the protection against PPRV infection. We additionally identified class I restricted immunogenic epitopes of PPRV in C57BL/6 mice. Our study therefore paves the way for an optimal utilization of this model to unravel PPRV pathogenesis and assessing the host correlates of protection.

immunology↗

bioRxiv2020

Antibody Response to a Nucleocapsid Epitope as a Marker for COVID-19 Disease Severity

Effective methods for predicting COVID-19 disease trajectories are urgently needed. Here, ELISA and coronavirus antigen microarray (COVAM) analysis mapped antibody epitopes in the plasma of COVID-19 patients (n = 86) experiencing a wide-range of disease states. The experiments identified antibodies to a 21-residue epitope from nucleocapsid (termed Ep9) associated with severe disease, including admission to the ICU, requirement for ventilators, or death. Importantly, anti-Ep9 antibodies can be detected within six days post-symptom onset and sometimes within one day. Furthermore, anti-Ep9 antibodies correlate with various comorbidities and hallmarks of immune hyperactivity. We introduce a simple-to-calculate, disease risk factor score to quantitate each patients comorbidities and age. For patients with anti-Ep9 antibodies, scores above 3.0 predict more severe disease outcomes with a 13.42 Likelihood Ratio (96.7% specificity). The results lay the groundwork for a new type of COVID-19 prognostic to allow early identification and triage of high-risk patients. Such information could guide more effective therapeutic intervention. Significance statementThe COVID-19 pandemic has resulted in over two million deaths worldwide. Despite efforts to fight the virus, the disease continues to overwhelm hospitals with severely ill patients. Diagnosis of COVID-19 is readily accomplished through a multitude of reliable testing platforms; however, prognostic prediction remains elusive. To this end, we identified a short epitope from the SARS-CoV-2 nucleocapsid protein and also a disease risk factor score based upon comorbidities and age. The presence of antibodies specifically binding to this epitope plus a score cutoff can predict severe COVID-19 outcomes with 96.7% specificity.

immunology↗

bioRxiv2020

Engineering lithoheterotrophy in an obligate chemolithoautotrophic Fe(II) oxidizing bacterium

Neutrophilic Fe(II) oxidizing bacteria like Mariprofundus ferrooxydans are obligate chemolithoautotrophic bacteria that play an important role in the biogeochemical cycling of iron and other elements in multiple environments. These bacteria generally exhibit a singular metabolic mode of growth which prohibits comparative "omics" studies. Furthermore, these bacteria are considered non-amenable to classical genetic methods due to low cell densities, the inability to form colonies on solid medium, and production of copious amounts of insoluble iron oxyhydroxides as their metabolic byproduct. Consequently, the functional understanding of these bacteria remains speculative despite the availability of substantial genomic information. Here we develop the first genetic system in neutrophilic Fe(II) oxidizing bacterium and use it to engineer lithoheterotrophy in M. ferrooxydans, a metabolism that has been speculated but not experimentally validated. Our work suggests that M. ferroxydans partitions energy generation from carbon oxidation. This synthetic biology approach could be extended to gain physiological understanding and domesticate other bacteria that grow using a single metabolic mode.

microbiology↗

bioRxiv2020

Distinct SARS-CoV-2 Antibody Reactivity Patterns in Coronavirus Convalescent Plasma Revealed by a Coronavirus Antigen Microarray

A coronavirus antigen microarray (COVAM) was constructed containing 11 SARS-CoV-2, 5 SARS-1, 5 MERS, and 12 seasonal coronavirus recombinant proteins. The array is designed to measure immunoglobulin isotype and subtype levels in serum or plasma samples against each of the individual antigens printed on the array. We probed the COVAM with COVID-19 convalescent plasma (CCP) collected from 99 donors who recovered from a PCR+ confirmed SARS-CoV-2 infection. The results were analyzed using two computational approaches, a generalized linear model (glm) and Random Forest (RF) prediction model, to classify individual specimens as either Reactive or Non-Reactive against the SARS-CoV-2 antigens. A training set of 88 pre-COVID-19 specimens (PreCoV) collected in August 2019 and102 positive specimens from SARS-CoV-2 PCR+ confirmed COVID-19 cases was used for these analyses. Results compared with an FDA emergency use authorized (EUA) SARS-CoV2 S1-based total Ig chemiluminescence immunoassay (Ortho Clinical Diagnostics VITROS(R) Anti-SARS-CoV-2 Total, CoV2T) and with a SARS-CoV-2 S1-S2 spike-based pseudovirus micro neutralization assay (SARS-CoV-2 reporter viral particle neutralization titration (RVPNT) showed high concordance between the 3 assays. Three CCP specimens that were negative by the VITROS CoV2T immunoassay were also negative by both COVAM and the RVPNT assay. Concordance between VITROS CoV2T and COVAM was 96%, VITROS CoV2T and RVPNT 93%, and RVPNT and COVAM 95%. The discordances were all weakly reactive samples near the cutoff threshold of the VITROS CoV2T immunoassay. The multiplex COVAM allows CCP to be grouped according to antibody reactivity patterns against 11 SARS-CoV-2 antigens. Unsupervised K-means analysis, via the gap statistics, as well as hierarchical clustering analysis revealed 3 main clusters with distinct reactivity intensities and patterns. These patterns were not recapitulated by adjusting the VITROS CoV2T or RVPNT assay thresholds. Plasma classified according to these reactivity patterns may be better associated with CCP treatment efficacy than antibody levels alone. The use of a SARS-CoV-2 antigen array may be useful to qualify CCP for administration as a treatment for acute COVID-19 and to interrogate vaccine immunogenicity and performance in preclinical and clinical studies to understand and recapitulate antibody responses associated with protection from infection and disease.

immunology↗

bioRxiv2020

Initial insights into the genetic epidemiology of SARS-CoV-2 isolates from Kerala suggest local spread from limited introductions

Coronavirus disease 2019 (COVID-19) rapidly spread from a city in China to almost every country in the world, affecting millions of individuals. Genomic approaches have been extensively used to understand the evolution and epidemiology of SARS-CoV-2 across the world. Kerala is a unique state in India well connected with the rest of the world through a large number of expatriates, trade, and tourism. The first case of COVID-19 in India was reported in Kerala in January 2020, during the initial days of the pandemic. The rapid increase in the COVID-19 cases in the state of Kerala has necessitated the understanding of the genetic epidemiology of circulating virus, evolution, and mutations in SARS-CoV-2. We sequenced a total of 200 samples from patients at a tertiary hospital in Kerala using COVIDSeq protocol at a mean coverage of 7,755X. The analysis identified 166 unique high-quality variants encompassing 4 novel variants and 89 new variants identified for the first time in SARS-CoV-2 samples isolated from India. Phylogenetic and haplotype analysis revealed that the circulating population of the virus was dominated (94.6% of genomes) by three distinct introductions followed by local spread, apart from identifying polytomies suggesting recent outbreaks. The genomes formed a monophyletic distribution exclusively mapping to the A2a clade. Further analysis of the functional variants revealed two variants in the S gene of the virus reportedly associated with increased infectivity and 5 variants that mapped to five primer/probe binding sites that could potentially compromise the efficacy of RT-PCR detection. To the best of our knowledge, this is the first and most comprehensive report of genetic epidemiology and evolution of SARS-CoV-2 isolates from Kerala.

genomics↗

bioRxiv2020

Unique mutational changes in SARS-CoV2 genome of different state of India

COVID-19 is a global pandemic causing more than 8 million deaths till mid-August, 2020. In India, more than 3 million confirmed cases have been reported although with relatively low death rate of 1.8%. In this study, we sequenced 47 genomes of SARS-CoV-2 from the patients of 13 districts of Uttar Pradesh (UP), the largest state of India using third-generation sequencing technique. The phylogenetic clustering revealed that no UP sample was aligned with the previously defined USA clade, where the mortality was high. We identified 56 distinct SNP variations in the genomes of UP resulting in a unique mutation rate of 1.19% per sequence, which is greater than the value 0.88% obtained for the rest of India. The relatively less death rate in UP indicates that the mutation in the virus is deleterious. Further investigation is required with larger sample size to determine the degree of virulence vis-a-vis SNP variation.

bioinformatics↗

bioRxiv2020

High throughput detection and genetic epidemiology of SARS-CoV-2 using COVIDSeq next generation sequencing

The rapid emergence of coronavirus disease 2019 (COVID-19) as a global pandemic affecting millions of individuals globally has necessitated sensitive and high-throughput approaches for the diagnosis, surveillance and for determining the genetic epidemiology of SARS-CoV-2. In the present study, we used the COVIDSeq protocol, which involves multiplex-PCR, barcoding and sequencing of samples for high-throughput detection and deciphering the genetic epidemiology of SARS-CoV-2. We used the approach on 752 clinical samples in duplicates, amounting to a total of 1536 samples which could be sequenced on a single S4 sequencing flow cell on NovaSeq 6000. Our analysis suggests a high concordance between technical duplicates and a high concordance of detection of SARS-CoV-2 between the COVIDSeq as well as RT-PCR approaches. An in-depth analysis revealed a total of six samples in which COVIDSeq detected SARS-CoV-2 in high confidence which were negative in RT-PCR. Additionally, the assay could detect SARS-CoV-2 in 21 samples and 16 samples which were classified inconclusive and pan-sarbeco positive respectively suggesting that COVIDSeq could be used as a confirmatory test. The sequencing approach also enabled insights into the evolution and genetic epidemiology of the SARS-CoV-2 samples. The samples were classified into a total of 3 clades. This study reports two lineages B.1.112 and B.1.99 for the first time in India. This study also revealed 1,143 unique single nucleotide variants and added a total of 73 novel variants identified for the first time. To the best of our knowledge, this is the first report of the COVIDSeq approach for detection and genetic epidemiology of SARS-CoV-2. Our analysis suggests that COVIDSeq could be a potential high sensitivity assay for detection of SARS-CoV-2, with an additional advantage of enabling genetic epidemiology of SARS-CoV-2.

genomics↗

bioRxiv2020

Analysis of the potential impact of genomic variants in SARS-CoV-2 genomes from India on molecular diagnostic assays

An isolated epidemic of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) causing Coronavirus Diseases (COVID-19) originating in Wuhan, China has now rapidly emerged into a global pandemic affecting millions of people worldwide. Molecular detection of SARS-CoV-2 using reverse transcription polymerase chain reaction (RT-PCR) forms the mainstay in screening, diagnosis and epidemiology of disease. The virus has been evolving through base substitutions. The recent availability of genomes of SARS-CoV-2 isolates from different countries including India motivated us to assess the presence and potential impact of variations in target sites for the oligonucleotide primers and probes used in molecular diagnosis. We catalogued a total of 132 primers or probes sequences from the literature and the public domain. Our analysis revealed a total of 125 unique genetic variants in 80 either primers or probes binding sites. A total of 13 unique variants had allele frequency of [≥] 1% in Indian SARS-CoV-2 genomes mapped to the primers or probes binding sites. A total of 15 primers or probes binding sites had cumulative variant frequency of [≥] 1% in the SARS-CoV-2 genomes. These included primers or probes sites which are widely used in India and across the world for molecular diagnosis as well as approved by national and international agencies. This highlights the need for sequencing genomes of emerging pathogens to make evidence based policies for development and approval of diagnostics. To the best of our knowledge, ours is the most comprehensive analysis of genomic variants in genomes of SARS-CoV-2 isolates from India and their potential impact on efficacy of molecular diagnostics.

genomics↗

bioRxiv2020

Protein Contact Map Denoising Using Generative Adversarial Networks

Protein residue-residue contact prediction from protein sequence information has undergone substantial improvement in the past few years, which has made it a critical driving force for building correct protein tertiary structure models. Improving accuracy of contact predictions has, therefore, become the forefront of protein structure prediction. Here, we show a novel contact map denoising method, ContactGAN, which uses Generative Adversarial Networks (GAN) to refine predicted protein contact maps. ContactGAN was able to make a consistent and significant improvement over predictions made by recent contact prediction methods when tested on two datasets including protein structure modeling targets in CASP13. ContactGAN will be a valuable addition in the structure prediction pipeline to achieve an extra gain in contact prediction accuracy.

bioinformatics↗

bioRxiv2020

Lineage recording reveals dynamics of cerebral organoid regionalization

Diverse regions develop within cerebral organoids generated from human induced pluripotent stem cells (iPSCs), however it has been a challenge to understand the lineage dynamics associated with brain regionalization. Here we establish an inducible lineage recording system that couples reporter barcodes, inducible CRISPR/Cas9 scarring, and single-cell transcriptomics to analyze lineage relationships during cerebral organoid development. We infer fate-mapped whole organoid phylogenies over a scarring time course, and reconstruct progenitor-neuron lineage trees within microdissected cerebral organoid regions. We observe increased fate restriction over time, and find that iPSC clones used to initiate organoids tend to accumulate in distinct brain regions. We use lineage-coupled spatial transcriptomics to resolve lineage locations as well as confirm clonal enrichment in distinctly patterned brain regions. Using long term 4-D light sheet microscopy to temporally track nuclei in developing cerebral organoids, we link brain region clone enrichment to positions in the neuroectoderm, followed by local proliferation with limited migration during neuroepithelial formation. Our data sheds light on how lineages are established during brain organoid regionalization, and our techniques can be adapted in any iPSC-derived cell culture system to dissect lineage alterations during perturbation or in patient-specific models of disease.Competing Interest StatementThe authors have declared no competing interest.View Full Text

developmental biology↗

bioRxiv2020

A Modular Microarray Imaging System for Highly Specific COVID-19 Antibody Testing

To detect the presence of antibodies in blood against SARS-CoV-2 in a highly sensitive and specific manner, here we describe a robust, inexpensive ($200), 3D-printable portable imaging platform (TinyArray imager) that can be deployed immediately in areas with minimal infrastructure to read coronavirus antigen microarrays (CoVAMs) that contain a panel of antigens from SARS-CoV-2, SARS-1, MERS, and other respiratory viruses. Application includes basic laboratories and makeshift field clinics where a few drops of blood from a finger prick could be rapidly tested in parallel for the presence of antibodies to SARS-CoV-2 with a test turnaround time of only 2-4 h. To evaluate our imaging device, we probed and imaged coronavirus microarrays with COVID-19-positive and negative sera and achieved a performance on par with a commercial microarray reader 100x more expensive than our imaging device. This work will enable large scale serosurveillance, which can play an important role in the months and years to come to implement efficient containment and mitigation measures, as well as help develop therapeutics and vaccines to treat and prevent the spread of COVID-19.

microbiology↗