Single-cell proteomics using mass spectrometry.

Over the past 2 to 3 years, mass-spectrometry-based single-cell proteomics (SCP) has experienced transformative improvements in microfluidic and robotic sample preparation, innovative MS1- and MS2-based multiplexing strategies, and specialized hardware (e.g., timsTOF Ultra 2, Astral), which have dramatically boosted sensitivity, throughput, and proteome coverage from picogram-level protein inputs.

Single-Cell Proteomics Using Mass Spectrometry.

Single-cell proteomics (SCP) is transforming our understanding of biological complexity by shifting from bulk proteomics, where signals are averaged over thousands of cells, to the proteome analysis of individual cells. This granular perspective reveals distinct cell states, population heterogeneity, and the underpinnings of disease pathogenesis that bulk approaches may obscure. However, SCP demands exceptional sensitivity, precise cell handling, and robust data processing to overcome the inherent challenges of analyzing picogram-level protein samples without amplification.

Single Cell Proteomics Reveals Novel Cell Phenotypes in Marfan Mouse Aneurysm.

Background: Single-cell omics technology is a powerful tool in biomedical research. However, single cell proteomics has lagged due to an inability to amplify peptides in a similar fashion to nucleotide strings. Single cell proteomics is important because proteins are the main functional unit in cells, and they often poorly correlate with mRNA quantities.

Cell Storage Conditions Impact Single-Cell Proteomic Landscapes.

Single cell transcriptomics (SCT) has revolutionized our understanding of cellular heterogeneity, yet the emergence of single cell proteomics (SCP) promises a more functional view of cellular dynamics. A challenge is that not all mass spectrometry facilities can perform SCP, and not all laboratories have access to cell sorting equipment required for SCP, which together motivate an interest in sending bulk cell samples through the mail for sorting and SCP analysis. Shipping requires cell storage, which has an unknown effect on SCP results.

Medications that Regulate Gastrointestinal Transit Influence Inpatient Blood Glucose.

Objective: A multitude of factors affect a hospitalized individual's blood glucose (BG), making BG difficult to predict and manage. Beyond medications well established to alter BG, such as beta-blockers, there are likely many medications with undiscovered effects on BG variability. Identification of these medications and the strength and timing of these relationships has potential to improve glycemic management and patient safety.

Differentiation between descending thoracic aortic diseases using machine learning and plasma proteomic signatures.

Background: Descending thoracic aortic aneurysms and dissections can go undetected until severe and catastrophic, and few clinical indices exist to screen for aneurysms or predict risk of dissection.

Methods: This study generated a plasma proteomic dataset from 75 patients with descending type B dissection (Type B) and 62 patients with descending thoracic aortic aneurysm (DTAA). Standard statistical approaches were compared to supervised machine learning (ML) algorithms to distinguish Type B from DTAA cases.

A Complete Workflow for High Throughput Human Single Skeletal Muscle Fiber Proteomics.

Skeletal muscle is a major regulatory tissue of whole-body metabolism and is composed of a diverse mixture of cell (fiber) types. Aging and several diseases differentially affect the various fiber types, and therefore, investigating the changes in the proteome in a fiber-type specific manner is essential. Recent breakthroughs in isolated single muscle fiber proteomics have started to reveal heterogeneity among fibers.

Simultaneous Multi-Omics Analysis by Direct Infusion Mass Spectrometry (SMAD-MS).

Combined multi-omics analysis of proteomics, polar metabolomics, and lipidomics requires separate liquid chromatography-mass spectrometry (LC-MS) platforms for each omics layer. This requirement for different platforms limits throughput and increases costs, preventing the application of mass spectrometry-based multi-omics to large scale drug discovery or clinical cohorts. Here, we present an innovative strategy for simultaneous multi-omics analysis by direct infusion (SMAD) using one single injection without liquid chromatography.

Complete Workflow for High Throughput Human Single Skeletal Muscle Fiber Proteomics.

Skeletal muscle is a major regulatory tissue of whole-body metabolism and is composed of a diverse mixture of cell (fiber) types. Aging and several diseases differentially affect the various fiber types, and therefore, investigating the changes in the proteome in a fiber-type specific manner is essential. Recent breakthroughs in isolated single muscle fiber proteomics have started to reveal heterogeneity among fibers.

Parallelization with Dual-Trap Single-Column Configuration Maximizes Throughput of Proteomic Analysis.

Proteomic analysis on the scale that captures population and biological heterogeneity over hundreds to thousands of samples requires rapid mass spectrometry methods, which maximize instrument utilization (IU) and proteome coverage while maintaining precise and reproducible quantification. To achieve this, a short liquid chromatography gradient paired to rapid mass spectrometry data acquisition can be used to reproducibly quantify a moderate set of analytes. High-throughput profiling at a limited depth is becoming an increasingly utilized strategy for tackling large sample sets but the time spent on loading the sample, flushing the column(s), and re-equilibrating the system reduces the ratio of meaningful data acquired to total operation time and IU.

Bias or biology? Importance of model interpretation in machine learning studies from electronic health records.

Objective: The rate of diabetic complication progression varies across individuals and understanding factors that alter the rate of complication progression may uncover new clinical interventions for personalized diabetes management.

Materials And Methods: We explore how various machine learning (ML) models and types of electronic health records (EHRs) can predict fast versus slow onset of neuropathy, nephropathy, ocular disease, or cardiovascular disease using only patient data collected prior to diabetes diagnosis.

Results: We find that optimized random forest models performed best to accurately predict the diagnosis of a diabetic complication, with the most effective model distinguishing between fast versus slow nephropathy (AUROC = 0.

Patterns of Prescribing Antiretroviral Therapy Upon Discharge to Psychiatry Inpatients With HIV/AIDS at a Large Urban Hospital.

Background: HIV infection is more prevalent among people with severe mental illness (SMI) than in the general population. People with SMI may lack access to recommended antiretroviral therapy (ART), and inpatient psychiatric admissions may be opportunities to ensure that individuals receive recommended treatment.

Objective: To evaluate ART prescription patterns on an inpatient psychiatry service.

Glycemic Control in Adult Surgical Patients Receiving Regular Insulin Added to Parenteral Nutrition vs Insulin Glargine: A Retrospective Chart Review.

Background: Hyperglycemia is a frequent complication in patients receiving parenteral nutrition (PN) and has been associated with an increased risk of mortality. Treatment of hyperglycemia requires insulin therapy; however, the optimal dose and route have not been established. This study aimed to compare regular insulin added to PN (RI-in-PN) with subcutaneous insulin glargine for the management of hyperglycemia in patients receiving PN.

Increasing HIV Testing in Inpatient Psychiatry.

Background: People with serious mental illness (SMI) are at elevated risk of HIV infection, but do not receive HIV tests regularly. Inpatient psychiatric admissions provide opportunities for HIV testing.

Objective: This study retrospectively examined the impact of three sequential interventions designed to increase HIV testing on an acute inpatient psychiatry service: (1) advocacy by an administrative champion, (2) an on-site HIV counselor, and (3) a clinician championing HIV testing.