Microbial Metagenomes Across a Complete Phytoplankton Bloom Cycle: High-Resolution Sampling Every 4 Hours Over 22 Days.

In May and June of 2021, marine microbial samples were collected for DNA sequencing in East Sound, WA, USA every 4 hours for 22 days. This high temporal resolution sampling effort captured the last 3 days of a Rhizosolenia sp. bloom, the initiation and complete bloom cycle of Chaetoceros socialis (8 days), and the following bacterial bloom (2 days).

Microbial Metagenomes Across a Complete Phytoplankton Bloom Cycle: High-Resolution Sampling Every 4 Hours Over 22 Days.

In May and June of 2021, marine microbial samples were collected for DNA sequencing in East Sound, WA, USA every 4 hours for 22 days. This high temporal resolution sampling effort captured the last 3 days of a sp. bloom, the initiation and complete bloom cycle of (8 days), and the following bacterial bloom (2 days).

A Framework for Quality Control in Quantitative Proteomics.

A thorough evaluation of the quality, reproducibility, and variability of bottom-up proteomics data is necessary at every stage of a workflow, from planning to analysis. We share vignettes applying adaptable quality control (QC) measures to assess sample preparation, system function, and quantitative analysis. System suitability samples are repeatedly measured longitudinally with targeted methods, and we share examples where they are used on three instrument platforms to identify severe system failures and track function over months to years.

Development of highly multiplex targeted proteomics assays in biofluids using the Stellar mass spectrometer.

The development of targeted assays that monitor biomedically relevant proteins is an important step in bridging discovery experiments to large scale clinical studies. Targeted assays are currently unable to scale to hundreds or thousands of targets. We demonstrate the generation of large-scale assays using a novel hybrid nominal mass instrument.

Data Independent Acquisition to Inform the Development of Targeted Proteomics Assays Using a Triple Quadrupole Mass Spectrometer.

Mass spectrometry based targeted proteomics methods provide sensitive and high-throughput analysis of selected proteins. To develop a targeted bottom-up proteomics assay, peptides must be evaluated as proxies for the measurement of a protein or proteoform in a biological matrix. Candidate peptide selection typically relies on predetermined biochemical properties, data from semi-stochastic sampling, or by empirical measurements.

Mag-Net: Rapid enrichment of membrane-bound particles enables high coverage quantitative analysis of the plasma proteome.

Membrane-bound particles in plasma are composed of exosomes, microvesicles, and apoptotic bodies and represent ~1-2% of the total protein composition. Proteomic interrogation of this subset of plasma proteins augments the representation of tissue-specific proteins, representing a "liquid biopsy," while enabling the detection of proteins that would otherwise be beyond the dynamic range of liquid chromatography-tandem mass spectrometry of unfractionated plasma. We have developed an enrichment strategy (Mag-Net) using hyper-porous strong-anion exchange magnetic microparticles to sieve membrane-bound particles from plasma.

Brain proteomic analysis implicates actin filament processes and injury response in resilience to Alzheimer's disease.

Resilience to Alzheimer's disease is an uncommon combination of high disease burden without dementia that offers valuable insights into limiting clinical impact. Here we assessed 43 research participants meeting stringent criteria, 11 healthy controls, 12 resilience to Alzheimer's disease and 20 Alzheimer's disease with dementia and analyzed matched isocortical regions, hippocampus, and caudate nucleus by mass spectrometry-based proteomics. Of 7115 differentially expressed soluble proteins, lower isocortical and hippocampal soluble Aβ levels is a significant feature of resilience when compared to healthy control and Alzheimer's disease dementia groups.

A peptide-centric quantitative proteomics dataset for the phenotypic assessment of Alzheimer's disease.

Alzheimer's disease (AD) is a looming public health disaster with limited interventions. Alzheimer's is a complex disease that can present with or without causative mutations and can be accompanied by a range of age-related comorbidities. This diverse presentation makes it difficult to study molecular changes specific to AD.

Putting Humpty Dumpty Back Together Again: What Does Protein Quantification Mean in Bottom-Up Proteomics?

Bottom-up proteomics provides peptide measurements and has been invaluable for moving proteomics into large-scale analyses. Commonly, a single quantitative value is reported for each protein-coding gene by aggregating peptide quantities into protein groups following protein inference or parsimony. However, given the complexity of both RNA splicing and post-translational protein modification, it is overly simplistic to assume that all peptides that map to a singular protein-coding gene will demonstrate the same quantitative response.

Accurately Assigning Peptides to Spectra When Only a Subset of Peptides Are Relevant.

The standard proteomics database search strategy involves searching spectra against a peptide database and estimating the false discovery rate (FDR) of the resulting set of peptide-spectrum matches. One assumption of this protocol is that all the peptides in the database are relevant to the hypothesis being investigated. However, in settings where researchers are interested in a subset of peptides, alternative search and FDR control strategies are needed.

High-Density Lipoprotein Carries Markers That Track With Recovery From Stroke.

Rationale: Prospective cohort studies question the value of HDL-C (high-density lipoprotein cholesterol) for stroke risk prediction.

Objective: Investigate the relationship between long-term functional recovery and HDL proteome and function.

Methods And Results: Changes in HDL protein composition and function (cholesterol efflux capacity) in patients after acute ischemic stroke at 2 time points (24 hours, 35 patients; 96 hours, 20 patients) and in 35 control subjects were measured.

GM-CSF driven myeloid cells in adipose tissue link weight gain and insulin resistance via formation of 2-aminoadipate.

In a GM-CSF driven myeloid cell deficient mouse model (Csf2) that has preserved insulin sensitivity despite increased adiposity, we used unbiased three-dimensional integration of proteome profiles, metabolic profiles, and gene regulatory networks to understand adipose tissue proteome-wide changes and their metabolic implications. Multi-dimensional liquid chromatography mass spectrometry and extended multiplex mass labeling was used to analyze proteomes of epididymal adipose tissues isolated from Csf2 and Csf2 mice that were fed low fat, high fat, or high fat plus cholesterol diets for 8 weeks. The metabolic health (as measured by body weight, adiposity, plasma fasting glucose, insulin, triglycerides, phospholipids, total cholesterol levels, and glucose and insulin tolerance tests) deteriorated with diet for both genotypes, while mice lacking Csf2 were protected from insulin resistance.

Extended Multiplexing of Tandem Mass Tags (TMT) Labeling Reveals Age and High Fat Diet Specific Proteome Changes in Mouse Epididymal Adipose Tissue.

The lack of high-throughput methods to analyze the adipose tissue protein composition limits our understanding of the protein networks responsible for age and diet related metabolic response. We have developed an approach using multiple-dimension liquid chromatography tandem mass spectrometry and extended multiplexing (24 biological samples) with tandem mass tags (TMT) labeling to analyze proteomes of epididymal adipose tissues isolated from mice fed either low or high fat diet for a short or a long-term, and from mice that aged on low high fat diets. The peripheral metabolic health (as measured by body weight, adiposity, plasma fasting glucose, insulin, triglycerides, total cholesterol levels, and glucose and insulin tolerance tests) deteriorated with diet and advancing age, with long-term high fat diet exposure being the worst.

PCSK9 Association With Lipoprotein(a).

Rationale: Lipoprotein(a) [Lp(a)] is a highly atherogenic low-density lipoprotein-like particle characterized by the presence of apoprotein(a) [apo(a)] bound to apolipoprotein B. Proprotein convertase subtilisin/kexin type 9 (PCSK9) selectively binds low-density lipoprotein; we hypothesized that it can also be associated with Lp(a) in plasma.

Objective: Characterize the association of PCSK9 and Lp(a) in 39 subjects with high Lp(a) levels (range 39-320 mg/dL) and in transgenic mice expressing either human apo(a) only or human Lp(a) (via coexpression of human apo(a) and human apolipoprotein B).