Biology subjects

Rock, J.

Publications and source records attributed to Rock, J..

9 recordsLinked to original sources

bioRxiv2024

Quantitating SARS-CoV-2 Neutralizing Antibodies from Human Dried Blood Spots

BackgroundIn the earliest days of COVID-19 pandemic, the collection of dried blood spots (DBS) enabled public health laboratories to undertake population-scale seroprevalence studies to estimate rates of SARS-CoV-2 exposure. With SARS-CoV-2 seropositivity levels now estimated to exceed 94% in the United States, attention has turned to using DBS to assess functional (neutralizing) antibodies within cohorts of interest. MethodsContrived DBS eluates from convalescent, fully vaccinated and pre-COVID-19 serum samples were evaluated in SARS-CoV-2 plaque reduction neutralization titer (PRNT) assays, a SARS-CoV-2 specific 8-plex microsphere immunoassay, a cell-based pseudovirus assay, and two different spike-ACE2 inhibition assays, an in-house Luminex-based RBD-ACE2 inhibition assay and a commercial real-time PCR-based inhibition assay (NAB-Sure). ResultsDBS eluates from convalescent individuals were compatible with the spike-ACE2 inhibition assays, but not cell-based pseudovirus assays or PRNT. However, the insensitivity of cell-based pseudovirus assays was overcome with DBS eluates from vaccinated individuals with high SARS-CoV-2 antibody titers. ConclusionSARS-CoV-2 neutralizing titers can be derived with confidence from DBS eluates, thereby opening the door to the use of these biospecimens for the analysis of vulnerable populations and normally hard to reach communities.

immunology↗

bioRxiv2023

A dose-response based model for statistical analysis of chemical genetic interactions in CRISPRi libraries

An important application of CRISPR interference (CRISPRi) technology is for identifying chemical-genetic interactions (CGIs). Discovery of genes that interact with exposure to antibiotics can yield insights to drug targets and mechanisms of action or resistance. The objective is to identify CRISPRi mutants whose relative abundance is suppressed (or enriched) in the presence of a drug when the target protein is depleted, reflecting synergistic behavior. Different sgRNAs for a given target can induce a wide range of protein depletion and differential effects on growth rate. The effect of sgRNA strength can be partially predicted based on sequence features. However, the actual growth phenotype depends on the sensitivity of cells to depletion of the target protein. For essential genes, sgRNA efficiency can be empirically measured by quantifying effects on growth rate. We observe that the most efficient sgRNAs are not always optimal for detecting synergies with drugs. sgRNA efficiency interacts in a non-linear way with drug sensitivity, producing an effect where the concentration-dependence is maximized for sgRNAs of intermediate strength (and less so for sgRNAs that induce too much or too little target depletion). To capture this interaction, we propose a novel statistical method called CRISPRi-DR (for Dose-Response model) that incorporates both sgRNA efficiencies and drug concentrations in a modified dose-response equation. We use CRISPRi-DR to re-analyze data from a recent CGI experiment in Mycobacterium tuberculosis to identify genes that interact with antibiotics. This approach can be generalized to non-CGI datasets, which we show via an CRISPRi dataset for E. coli growth on different carbon sources. The performance is competitive with the best of several related analytical methods. However, for noisier datasets, some of these methods generate far more significant interactions, likely including many false positives, whereas CRISPRi-DR maintains higher precision, which we observed in both empirical and simulated data. Author SummaryCRISPRi technology is revolutionizing research in various areas of the life sciences, including microbiology, affording the ability to partially deplete the expression of target proteins in a specific and controlled way. Among the applications of CRISPRi, it can be used to construct large (even genome-wide) libraries of knock-down mutants for profiling antibacterial inhibitors and identifying chemical-genetic interactions (CGIs), which can yield insights on drug targets and mechanisms of action and resistance. The data generated by these experiments (i.e., sgRNA counts from high throughput sequencing) is voluminous and subject to various sources of noise. The goal of statistical analysis of such data is to identify significant CGIs, which are genes whose depletion sensitizes cells to an inhibitor. In this paper, we show how to incorporate both sgRNA efficiency and drug concentration simultaneously in a model (CRISPRi-DR) based on an extension of the classic dose-response (Hill) equation in enzymology. This model has advantages over other analytical methods for CRISPRi, which we show using empirical and simulated data.

bioinformatics↗

bioRxiv2023

Scalable querying of human cell atlases via a foundational model reveals commonalities across fibrosis-associated macrophages

Single-cell RNA-seq (scRNA-seq) studies have profiled over 100 million human cells across diseases, developmental stages, and perturbations to date. A singular view of this vast and growing expression landscape could help reveal novel associations between cell states and diseases, discover cell states in unexpected tissue contexts, and relate in vivo cells to in vitro models. However, these require a common, scalable representation of cell profiles from across the body, a general measure of their similarity, and an efficient way to query these data. Here, we present SCimilarity, a metric learning framework to learn and search a unified and interpretable representation that annotates cell types and instantaneously queries for a cell state across tens of millions of profiles. We demonstrate SCimilarity on a 22.7 million cell corpus assembled across 399 published scRNA-seq studies, showing accurate integration, annotation and querying. We experimentally validated SCimilarity by querying across tissues for a macrophage subset originally identified in interstitial lung disease, and showing that cells with similar profiles are found in other fibrotic diseases, tissues, and a 3D hydrogel system, which we then repurposed to yield this cell state in vitro. SCimilarity serves as a foundational model for single cell gene expression data and enables researchers to query for similar cellular states across the entire human body, providing a powerful tool for generating novel biological insights from the growing Human Cell Atlas.

bioinformatics↗

bioRxiv2022

Structural and functional basis of the universal transcription factor NusG pro-pausing activity in Mycobacterium tuberculosis

Transcriptional pauses mediate regulation of RNA biogenesis. DNA-encoded pause signals trigger elemental pausing by stabilizing a half-translocated (RNA-not-DNA) state and by promoting RNAP swiveling that other factors can enhance. The universal transcription factor NusG (Spt5 in eukaryotes and archaea) N-terminal domain (NGN) modulates pausing through contacts to RNAP and DNA. Pro-pausing NusGs (e.g., Bacillus subtilis) enhance some pauses whereas anti-pausing NusGs (e.g., Escherichia coli) suppress some pauses. Little is known about pausing and NusG in the human pathogen Mycobacterium tuberculosis (Mtb). Using biochemistry and cryo-electron microscopy, we show that MtbNusG is a pro-pausing NusG that captures paused, swiveled RNAP by contacts to the RNAP protrusion and to a nontemplate strand-DNA wedge inserted between the NGN and the RNAP gate loop. On the other hand, we find that anti-pausing E. coli NGN contacts the RNAP gate loop to inhibit swiveling and pausing of MtbRNAP. Using CRISPR-mediated mycobacterial genetics, we show that a pro-pausing NGN is required to support robust mycobacterial growth. Our results define an essential function of NusG in mycobacteria and the structural basis of pro-vs. anti-pausing NusG activity with broad implications for NusG function in all domains of life.

molecular biology↗

bioRxiv2022

Developmental spontaneous activity promotes sensory domains, frequency tuning and proper gain in central auditory circuits

Neurons that process sensory information exhibit bursts of electrical activity during development, providing early training to circuits that will later encode similar features of the external world. In the mammalian auditory system, this intrinsically generated activity emerges from the cochlea prior to hearing onset, but its role in maturation of auditory circuitry remains poorly understood. We show that selective disruption of cochlear supporting cell spontaneous activity suppressed patterned burst firing of central auditory neurons without impacting cell survival or acoustic thresholds. However, neurons within the inferior colliculus of these mice exhibited enhanced acoustic sensitivity and broader frequency tuning, resulting in wider isofrequency lamina. Despite this enhanced neural responsiveness, total tone-responsive regions of the midbrain and cortex were substantially smaller. Thus, loss of pre-hearing cochlear activity causes profound changes in neural encoding of sound, with important implications for restoration of hearing in individuals that experience disrupted activity during this critical developmental period.

neuroscience↗

bioRxiv2022

The Ca2+-gated Cl- channel TMEM16A amplifies capillary pericyte contraction reducing cerebral blood flow after ischemia

Pericyte-mediated capillary constriction decreases cerebral blood flow in stroke after an occluded artery is unblocked. The determinants of pericyte tone are poorly understood. We show that a small rise in cytoplasmic Ca2+ concentration ([Ca2+]i) in pericytes activates chloride efflux through the Ca2+-gated anion channel TMEM16A, thus depolarizing the cell and opening voltage-gated calcium channels. This mechanism strongly amplifies the pericyte [Ca2+]i rise and capillary constriction evoked by contractile agonists and ischemia. In a rodent stroke model, TMEM16A inhibition slows the ischemia-evoked pericyte [Ca2+]i rise, capillary constriction and pericyte death, reduces neutrophil stalling and improves cerebrovascular reperfusion. Genetic analysis implicates altered TMEM16A expression in poor patient recovery from ischemic stroke. Thus, pericyte TMEM16A is a crucial regulator of cerebral capillary function, and a potential therapeutic target for stroke and possibly other disorders of impaired microvascular flow, such as Alzheimers disease and vascular dementia.

physiology↗

bioRxiv2020

DNA Methylation-based Signatures Classify Sporadic Pituitary Tumors According to Clinicopathological Features.

BackgroundDistinct genome-wide methylation patterns have consistently clustered pituitary neuroendocrine tumors (PT) into molecular groups associated with specific clinicopathological features. Here we aim to identify, characterize and validate the methylation signatures that objectively classify PT into those molecular groups. MethodsCombining in-house and publicly available data, we conducted an analysis of the methylome profile of a comprehensive cohort of 177 tumor and 20 non-tumor specimens from the pituitary gland. We also retrieved methylome data from an independent pituitary tumor (PT) cohort (N=86) to validate our findings. ResultsWe identified three methylation clusters associated with functional status and adenohypophyseal cell lineages using an unsupervised approach. We also identified signatures based on differentially methylated CpG probes (DMP), some of which overlapped with pituitary-specific transcription factors genes (SF1 and Tpit), that significantly distinguished pairs of clusters related to functional status and adenohypophyseal cell lineage. These findings were reproduced in an independent cohort, validating these methylation signatures. The DMPs were mainly annotated in enhancer regions associated with pathways and genes involved in cell identity and tumorigenesis. ConclusionsWe identified and validated methylation signatures that distinguished PT by distinct functional status and adenohypophyseal cell lineages. These signatures, annotated in enhancer regions, indicate the importance of these elements in pituitary tumorigenesis. They also provide an unbiased approach to classify pituitary tumors according to the most recent classification recommended by the WHO 2017 using methylation profiling. Key-pointsO_LIDistinct methylation landscapes define PT groups with specific functional status/subtypes and adenohypophyseal lineages subtypes. C_LIO_LIMethylation abnormalities in each cluster mainly occur in CpG annotated in distal regions overlapping predicted enhancers regions associated with pathways and genes involved in cell identity and tumorigenesis. C_LIO_LIDNA methylation signatures provide an unbiased approach to classify PT. C_LI Importance of the studyThis study harnessed the largest methylome data to date from a comprehensive cohort of pituitary specimens obtained from four different institutions. We identified and validated methylation signatures that distinguished pituitary tumors into molecular groups that reflect the functionality and adenohypophyseal cell lineages of these tumors. These signatures, mainly located in enhancers, are associated with pathways and genes involved in cell identity and tumorigenesis. Our results show that methylome profiling provides an objective approach to classify PT according to the most recent classification of PT recommended by the 2017 WHO.

cancer biology↗

bioRxiv2019

Detection of glioma and prognostic subtypes by non-invasive circulating cell-free DNA methylation markers

Genome-wide DNA methylation profiling has shown that epigenetic abnormalities are biologically important in glioma and can be used to classify these tumors into distinct prognostic groups. Thus far, DNA profiling has required surgically resected glioma tissue; however, gliomas release tumoral material into biofluids, such as blood and cerebrospinal fluid, providing an opportunity for a minimally invasive testing. While prior studies have shown that genetic and epigenetic markers can be detected in blood or cerebrospinal fluid (e.g., liquid biopsy [LB]), there has been low sensitivity for tumor-specific markers. We hypothesize that the low sensitivity is due to the targeted assay methods. Therefore, we profiled the genome-wide CpG methylation levels in DNA of tumor tissue and cell-free DNA in serum of glioma patients, to identify non-invasive epigenetic LB (eLB) markers in the serum that reflect the characteristics of the tumor tissue. From the epigenetic profiles of serum from patients diagnosed with glioma (N=15 IDH mutant and N=7 IDH wildtype) and with epilepsy (N=3), we defined glioma-specific and IDH-specific eLB signatures (Glioma-eLB and IDH-eLB, respectively). The epigenetic profiles of the matched tissue demonstrate that these eLB signatures reflected the signature of the tumor. Through cross-validation we show that Glioma-eLB can accurately predict a patients glioma from those with other neoplasias (N=6 Colon; N=14 Pituitary; N=3 Breast; N=4 Lung), non-neoplastic immunological conditions (N=22 sepsis; N=9 pancreatic islet transplantation), and from healthy individuals (sensitivity: 98%; specificity: 99%). Finally, IDH-eLB includes promoter methylated markers associated with genes known to be involved in glioma tumorigenesis (PVT1 and CXCR6). The application of the non-invasive eLB signature discovered in this study has the potential to complement the standard of care for patients harboring glioma.

cancer biology↗

bioRxiv2019

Two accessory proteins govern MmpL3 mycolic acid transport in mycobacteria

Mycolic acids are the signature lipid of mycobacteria and constitute an important physical component of the cell wall, a target of mycobacterial specific antibiotics, and a mediator of M. tuberculosis pathogenesis. Mycolic acids are synthesized in the cytoplasm and are thought to be transported to the cell wall as a trehalose ester by the MmpL3 transporter, an antibiotic target for M. tuberculosis. However, the mechanism by which mycolate synthesis is coupled to transport, and the full MmpL3 transport machinery, is unknown. Here we identify two new components of the MmpL3 transport machinery in mycobacteria. The protein encoded by MSMEG_0736/Rv0383c is essential for growth of M. smegmatis and M. tuberculosis, is anchored to the cytoplasmic membrane, physically interacts with and colocalizes with MmpL3 in growing cells, and is required for trehalose monomycolate transport to the cell wall. In light of these findings we propose Msmeg_0736/Rv0383c be named \"TMM transport factor A\", TtfA. The protein encoded by MSMEG_5308 also interacts with the MmpL3 complex, but is nonessential for growth or TMM transport. However, MSMEG_5308 accumulates with inhibition of MmpL3 mediated TMM transport and stabilizes the MmpL3/TtfA complex, indicating that it stabilizes the transport system during stress. These studies identify two new components of the mycobacterial mycolate transport machinery, an emerging antibiotic target in M. tuberculosis.

microbiology↗