Biology subjects

Weitz, K. K.

Publications and source records attributed to Weitz, K. K..

4 recordsLinked to original sources

bioRxiv2025

Improved surfactant-assisted one-pot sample preparation for robust convenient single cell proteomics

Recent advances in mass spectrometry-based single-cell proteomics (SCP) technologies have revolutionized the SCP field for comprehensive characterization of cellular heterogeneity. However, most of the current SCP approaches employ sub-{micro}L to 1 {micro}L processing volume for effective single-cell sample preparation using either ultralow-volume specialized devices or a 384-well plate by frequently adding water to the plate well to compensate water evaporation, which greatly limits their broad accessibility and analytical robustness. Here we report a robust convenient SCP method termed iSOP (improved Surfactant-assisted One-Pot processing) for processing of single cells at the low {micro}L processing volume using the 384-well plate with tight sealing to avoid sample drying loss. This iSOP SCP method was built upon our previously developed SOP method by the replacement of a PCR tube or 96-well plate with the low-volume 384-well plate and systematic optimization of the single-cell processing conditions. After optimization, 3 {micro}L was selected as the processing volume with a mixture of 2 ng trypsin and 2 ng Lys-C enzymes in terms of robustness, detection sensitivity, and operation convenience. With a commonly accessible LC-MS platform, iSOP-MS can detect and quantify [~]1,200-1,800 protein groups from single HeLa or MCF7 cells. Application of iSOP-MS to two neuroblastoma cell lines has demonstrated that iSOP-MS enabled reliable identification of an average of [~]1,700 and [~]2,050 protein groups from single BE2-C and SK-N-SH cells, respectively, and precise characterization of cellular heterogeneity between the two distinct cell types and within the same cell type. When compared to other available SCP methods, iSOP-MS is more robust and convenient for routine, cost-effective quantitative SCP analysis.

biochemistry↗

bioRxiv2024

Dysregulation of lung epithelial cell homeostasis and immunity contributes to Middle East Respiratory Syndrome coronavirus disease severity

Coronaviruses (CoV) emerge suddenly from animal reservoirs to cause novel diseases in new hosts. Discovered in 2012, Middle East respiratory syndrome coronavirus (MERS-CoV) is endemic in camels in the Middle East and is continually causing local outbreaks and epidemics. While all three newly emerging human CoV from past 20 years (SARS-CoV, SARS-CoV-2, MERS-CoV) cause respiratory disease, each CoV has unique host interactions that drive differential pathogeneses. To better understand the virus and host interactions driving lethal MERS-CoV infection, we performed a longitudinal multi-omics analysis of sublethal and lethal MERS-CoV infection in mice. Significant differences were observed in body weight loss, virus titers and acute lung injury among lethal and sub-lethal virus doses. Virus induced apoptosis of type I and II alveolar epithelial cells suggest that loss or dysregulation of these key cell populations was a major driver of severe disease. Omics analysis suggested differential pathogenesis was multi-factorial with clear differences among innate and adaptive immune pathways as well as those that regulate lung epithelial homeostasis. Infection of mice lacking functional T and B-cells showed that adaptive immunity was important in controlling viral replication but also increased pathogenesis. In summary, we provide a high-resolution host response atlas for MERS-CoV infection and disease severity. Multi-omics studies of viral pathogenesis offer a unique opportunity to not only better understand the molecular mechanisms of disease but also to identify genes and pathways that can be exploited for therapeutic intervention all of which is important for our future pandemic preparedness. ImportanceEmerging coronaviruses like SARS-CoV, SARS-CoV-2 and MERS-CoV cause a range of disease outcomes in humans from asymptomatic, moderate and severe respiratory disease which can progress to death but the factors causing these disparate outcomes remain unclear. Understanding host responses to mild and life-threatening infection provides insight into virus-host networks within and across organ systems that contribute to disease outcomes. We used multi-omics approaches to comprehensively define the host response to moderate and severe MERS-CoV infection. Severe respiratory disease was associated with dysregulation of the immune response. Key lung epithelial cell populations that are essential for lung function get infected and die. Mice lacking key immune cell populations experienced greater virus replication but decreased disease severity implicating the immune system in both protective and pathogenic roles in the response to MERS-CoV. These data could be utilized to design new therapeutic strategies targeting specific pathways that contribute to severe disease.

microbiology↗

bioRxiv2021

Utilizing proteomics and phosphoproteomics to predict ex vivo drug sensitivity across genetically diverse AML patients

Acute Myeloid Leukemia (AML) affects 20,000 patients in the US annually with a five-year survival rate of approximately 25%. One reason for the low survival rate is the high prevalence of clonal evolution that gives rise to heterogeneous sub-populations of leukemia. This genetic heterogeneity is difficult to treat using conventional therapies that are generally based on the detection of a single driving mutation. Thus, the use of molecular signatures, consisting of multiple functionally related transcripts or proteins, in making treatment decisions may overcome this hurdle and provide a more effective way to inform drug treatment protocols. Toward this end, the Beat AML research program prospectively collected genomic and transcriptomic data from over 1000 AML patients and carried out ex vivo drug sensitivity assays to identify signatures that could predict patient-specific drug responses. The Clinical Proteomic Tumor Analysis Consortium is in the process of extending this cohort to collect proteomic and phosphoproteomic measurements from a subset of these patient samples to evaluate the hypothesis that proteomic signatures can robustly predict drug response in AML patients. We sought to examine this hypothesis on a sub-cohort of 38 patient samples from Beat AML with proteomic and drug response data and evaluate our ability to identify proteomic signatures that predict drug response with high accuracy. For this initial analysis we built predictive models of patient drug responses across 26 drugs of interest using the proteomics and phosphproteomics data. We found that proteomics-derived signatures provide an accurate and robust signature of drug response in the AML ex vivo samples, as well as related cell lines, with better performance than those signatures derived from mutations or mRNA expression. Furthermore, we found that in specific drug-resistant cell lines, the proteins in our prognostic signatures represented dysregulated signaling pathways compared to parental cell lines, confirming the role of the proteins in the signatures in drug resistance. In conclusion, this pilot study demonstrates strong promise for proteomics-based patient stratification to predict drug sensitivity in AML.

bioinformatics↗

bioRxiv2020

A lipid metabolic map of the pathogenic fungus Histoplasma capsulatum

Lipids play a fundamental role in fungal cell biology, being essential cell membrane components and major targets of antifungal drugs. A deeper knowledge of lipid metabolism is key for developing new drugs and a better understanding of fungal pathogenesis. Here we built a comprehensive map of the Histoplasma capsulatum lipid metabolic pathway by incorporating proteomic and lipidomic analyses. We performed genetic complementation and overexpression of H. capsulatum genes in Saccharomyces cerevisiae to validate reactions identified in the map and to determine enzymes responsible for catalyzing orphan reactions. The map led to the identification of both the fatty acid desaturation and the sphingolipid biosynthesis pathways as targets for drug development. We found that the sphingolipid biosynthesis inhibitor myriocin, the fatty acid desaturase inhibitor thiocarlide and the fatty acid analog 10-thiastearic acid inhibit H. capsulatum growth in nanomolar to low micromolar concentrations. These compounds also reduced the intracellular infection in an alveolar macrophage cell line. Overall, this lipid metabolic map revealed pathways that can be targeted for drug development.

microbiology↗