A male steroid controls female sexual behaviour in the malaria mosquito.

Insects, unlike vertebrates, are widely believed to lack male-biased sex steroid hormones1. In the malaria mosquito Anopheles gambiae, the ecdysteroid 20-hydroxyecdysone (20E) appears to have evolved to both control egg development when synthesized by females2 and to induce mating refractoriness when sexually transferred by males3. Because egg development and mating are essential reproductive traits, understanding how Anopheles females integrate these hormonal signals can spur the design of new malaria control programs. Here we reveal that these reproductive functions are regulated by distinct sex steroids through a sophisticated network of ecdysteroid-activating/inactivating enzymes. We identify a male-specific oxidized ecdysteroid, 3-dehydro-20E (3D20E), which safeguards paternity by turning off female sexual receptivity following its sexual transfer and activation by dephosphorylation. Notably, 3D20E transfer also induces expression of a reproductive gene that preserves egg development during Plasmodium infection, ensuring fitness of infected females. Female-derived 20E does not trigger sexual refractoriness but instead licenses oviposition in mated individuals once a 20E-inhibiting kinase is repressed. Identifying this male-specific insect steroid hormone and its roles in regulating female sexual receptivity, fertility and interactions with Plasmodium parasites suggests the possibility for reducing the reproductive success of malaria-transmitting mosquitoes.

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. Internal QCs incorporated at the protein and peptide levels allow our team to assess sample preparation issues and to differentiate system failures from sample-specific issues. External QC samples prepared alongside our experimental samples are used to verify the consistency and quantitative potential of our results during batch correction and normalization before assessing biological phenotypes. We combine these controls with rapid analysis (Skyline), longitudinal QC metrics (AutoQC), and server-based data deposition (PanoramaWeb). We propose that this integrated approach to QC is a useful starting point for groups to facilitate rapid quality control assessment to ensure that valuable instrument time is used to collect the best quality data possible. Data are available on Panorama Public and ProteomeXchange under the identifier PXD051318.

Does Data-Independent Acquisition Data Contain Hidden Gems? A Case Study Related to Alzheimer's Disease.

One of the potential benefits of using data-independent acquisition (DIA) proteomics protocols is that information not originally targeted by the study may be present and discovered by subsequent analysis. Herein, we reanalyzed DIA data originally recorded for global proteomic analysis to look for isomerized peptides, which occur as a result of spontaneous chemical modifications to long-lived proteins. Examination of a large set of human brain samples revealed a striking relationship between Alzheimer's disease (AD) status and isomerization of aspartic acid in a peptide from tau. Relative to controls, a surprising increase in isomer abundance was found in both autosomal dominant and sporadic AD samples. To explore potential mechanisms that might account for these observations, quantitative analysis of proteins related to isomerization repair and autophagy was performed. Differences consistent with reduced autophagic flux in AD-related samples relative to controls were found for numerous proteins, including most notably p62, a recognized indicator of autophagic inhibition. These results suggest, but do not conclusively demonstrate, that lower autophagic flux may be strongly associated with loss of function in AD brains. This study illustrates that DIA data may contain unforeseen results of interest and may be particularly useful for pilot studies investigating new research directions. In this case, a promising target for future investigations into the therapy and prevention of AD has been identified.

Proteomics support the threespine stickleback egg coat as a protective oocyte envelope.

Ancestrally marine threespine stickleback fish (Gasterosteus aculeatus) have undergone an adaptive radiation into freshwater environments throughout the Northern Hemisphere, creating an excellent model system for studying molecular adaptation and speciation. Ecological and behavioral factors have been suggested to underlie stickleback reproductive isolation and incipient speciation, but reproductive proteins mediating gamete recognition during fertilization have so far remained unexplored. To begin to investigate the contribution of reproductive proteins to stickleback reproductive isolation, we have characterized the stickleback egg coat proteome. We find that stickleback egg coats are comprised of homologs to the zona pellucida (ZP) proteins ZP1 and ZP3, as in other teleost fish. Our molecular evolutionary analyses indicate that across teleosts, ZP3 but not ZP1 has experienced positive Darwinian selection. Mammalian ZP3 is also rapidly evolving, and surprisingly some residues under selection in stickleback and mammalian ZP3 directly align. Despite broad homology, however, we find differences between mammalian and stickleback ZP proteins with respect to glycosylation, disulfide bonding, and sites of synthesis. Taken together, the changes we observe in stickleback ZP protein architecture suggest that the egg coats of stickleback fish, and perhaps fish more generally, have evolved to fulfill a more protective functional role than their mammalian counterparts.

Glucocerebrosidase deficiency promotes protein aggregation through dysregulation of extracellular vesicles.

Mutations in the glucosylceramidase beta (GBA) gene are strongly associated with neurodegenerative diseases marked by protein aggregation. GBA encodes the lysosomal enzyme glucocerebrosidase, which breaks down glucosylceramide. A common explanation for the link between GBA mutations and protein aggregation is that lysosomal accumulation of glucosylceramide causes impaired autophagy. We tested this hypothesis directly by measuring protein turnover and abundance in Drosophila mutants with deletions in the GBA ortholog Gba1b. Proteomic analyses revealed that known autophagy substrates, which had severely impaired turnover in autophagy-deficient Atg7 mutants, showed little to no overall slowing of turnover or increase in abundance in Gba1b mutants. Likewise, Gba1b mutants did not have the marked impairment of mitochondrial protein turnover seen in mitophagy-deficient parkin mutants. Proteasome activity, microautophagy, and endocytic degradation also appeared unaffected in Gba1b mutants. However, we found striking changes in the turnover and abundance of proteins associated with extracellular vesicles (EVs), which have been proposed as vehicles for the spread of protein aggregates in neurodegenerative disease. These changes were specific to Gba1b mutants and did not represent an acceleration of normal aging. Western blotting of isolated EVs confirmed the increased abundance of EV proteins in Gba1b mutants, and nanoparticle tracking analysis revealed that Gba1b mutants had six times as many EVs as controls. Genetic perturbations of EV production in Gba1b mutants suppressed protein aggregation, demonstrating that the increase in EV abundance contributed to the accumulation of protein aggregates. Together, our findings indicate that glucocerebrosidase deficiency causes pathogenic changes in EV metabolism and may promote the spread of protein aggregates through extracellular vesicles.

Data-Independent Acquisition Mass Spectrometry To Quantify Protein Levels in FFPE Tumor Biopsies for Molecular Diagnostics.

Mass spectrometry-based protein quantitation is currently used to measure therapeutically relevant protein biomarkers in CAP/CLIA setting to predict likely responses of known therapies. Selected reaction monitoring (SRM) is the method of choice due to its outstanding analytical performance. However, data-independent acquisition (DIA) is now emerging as a proteome-scale clinical assay. We evaluated the ability of DIA to profile the patient-specific proteomes of sample-limited tumor biopsies and to quantify proteins of interest in a targeted fashion using formalin-fixed, paraffin-embedded (FFPE) tumor biopsies ( n = 12) selected from our clinical laboratory. DIA analysis on the tumor biopsies provided 3713 quantifiable proteins including actionable biomarkers currently in clinical use, successfully separated two gastric cancers from colorectal cancer specimen solely on the basis of global proteomic profiles, and identified subtype-specific proteins with prognostic or diagnostic value. We demonstrate the potential use of DIA-based quantitation to inform therapeutic decision-making using TUBB3, for which clinical cutoff expression levels have been established by SRM. Comparative analysis of DIA-based proteomic profiles and mRNA expression levels found positively and negatively correlated protein-gene pairs, a finding consistent with previously reported results from fresh-frozen tumor tissues.

The EARP Complex and Its Interactor EIPR-1 Are Required for Cargo Sorting to Dense-Core Vesicles.

The dense-core vesicle is a secretory organelle that mediates the regulated release of peptide hormones, growth factors, and biogenic amines. Dense-core vesicles originate from the trans-Golgi of neurons and neuroendocrine cells, but it is unclear how this specialized organelle is formed and acquires its specific cargos. To identify proteins that act in dense-core vesicle biogenesis, we performed a forward genetic screen in Caenorhabditis elegans for mutants defective in dense-core vesicle function. We previously reported the identification of two conserved proteins that interact with the small GTPase RAB-2 to control normal dense-core vesicle cargo-sorting. Here we identify several additional conserved factors important for dense-core vesicle cargo sorting: the WD40 domain protein EIPR-1 and the endosome-associated recycling protein (EARP) complex. By assaying behavior and the trafficking of dense-core vesicle cargos, we show that mutants that lack EIPR-1 or EARP have defects in dense-core vesicle cargo-sorting similar to those of mutants in the RAB-2 pathway. Genetic epistasis data indicate that RAB-2, EIPR-1 and EARP function in a common pathway. In addition, using a proteomic approach in rat insulinoma cells, we show that EIPR-1 physically interacts with the EARP complex. Our data suggest that EIPR-1 is a new interactor of the EARP complex and that dense-core vesicle cargo sorting depends on the EARP-dependent trafficking of cargo through an endosomal sorting compartment.

Integrative phenomics reveals insight into the structure of phenotypic diversity in budding yeast.

To better understand the quantitative characteristics and structure of phenotypic diversity, we measured over 14,000 transcript, protein, metabolite, and morphological traits in 22 genetically diverse strains of Saccharomyces cerevisiae. More than 50% of all measured traits varied significantly across strains [false discovery rate (FDR) = 5%]. The structure of phenotypic correlations is complex, with 85% of all traits significantly correlated with at least one other phenotype (median = 6, maximum = 328). We show how high-dimensional molecular phenomics data sets can be leveraged to accurately predict phenotypic variation between strains, often with greater precision than afforded by DNA sequence information alone. These results provide new insights into the spectrum and structure of phenotypic diversity and the characteristics influencing the ability to accurately predict phenotypes.

Multiplexed MS/MS for improved data-independent acquisition.

In mass spectrometry-based proteomics, data-independent acquisition (DIA) strategies can acquire a single data set useful for both identification and quantification of detectable peptides in a complex mixture. However, DIA data are noisy owing to a typical five- to tenfold reduction in precursor selectivity compared to data obtained with data-dependent acquisition or selected reaction monitoring. We demonstrate a multiplexing strategy, MSX, for DIA analysis that increases precursor selectivity fivefold.

The PINK1-Parkin pathway promotes both mitophagy and selective respiratory chain turnover in vivo.

The accumulation of damaged mitochondria has been proposed as a key factor in aging and the pathogenesis of many common age-related diseases, including Parkinson disease (PD). Recently, in vitro studies of the PD-related proteins Parkin and PINK1 have found that these factors act in a common pathway to promote the selective autophagic degradation of damaged mitochondria (mitophagy). However, whether Parkin and PINK1 promote mitophagy under normal physiological conditions in vivo is unknown. To address this question, we used a proteomic approach in Drosophila to compare the rates of mitochondrial protein turnover in parkin mutants, PINK1 mutants, and control flies. We found that parkin null mutants showed a significant overall slowing of mitochondrial protein turnover, similar to but less severe than the slowing seen in autophagy-deficient Atg7 mutants, consistent with the model that Parkin acts upstream of Atg7 to promote mitophagy. By contrast, the turnover of many mitochondrial respiratory chain (RC) subunits showed greater impairment in parkin than Atg7 mutants, and RC turnover was also selectively impaired in PINK1 mutants. Our findings show that the PINK1-Parkin pathway promotes mitophagy in vivo and, unexpectedly, also promotes selective turnover of mitochondrial RC subunits. Failure to degrade damaged RC proteins could account for the RC deficits seen in many PD patients and may play an important role in PD pathogenesis.

Proteogenomic database construction driven from large scale RNA-seq data.

The advent of inexpensive RNA-seq technologies and other deep sequencing technologies for RNA has the promise to radically improve genomic annotation, providing information on transcribed regions and splicing events in a variety of cellular conditions. Using MS-based proteogenomics, many of these events can be confirmed directly at the protein level. However, the integration of large amounts of redundant RNA-seq data and mass spectrometry data poses a challenging problem. Our paper addresses this by construction of a compact database that contains all useful information expressed in RNA-seq reads. Applying our method to cumulative C. elegans data reduced 496.2 GB of aligned RNA-seq SAM files to 410 MB of splice graph database written in FASTA format. This corresponds to 1000× compression of data size, without loss of sensitivity. We performed a proteogenomics study using the custom data set, using a completely automated pipeline, and identified a total of 4044 novel events, including 215 novel genes, 808 novel exons, 12 alternative splicings, 618 gene-boundary corrections, 245 exon-boundary changes, 938 frame shifts, 1166 reverse strands, and 42 translated UTRs. Our results highlight the usefulness of transcript + proteomic integration for improved genome annotations.

A second X chromosome improves cognition in aging male and female mice.

Women show resilience to cognitive aging, in the absence of dementia, in many populations. To dissect sex differences, we utilized the FCG and XY* mouse models. Female gonads and sex chromosomes improved cognition in aging mice of both sexes. Further, presence of a second X in male and female mice conferred cognitive resilience while its absence in females blocked it. In the hippocampal proteome of aging female mice, the second X increased proteins involved in synaptogenesis signaling - a potential pathway to improved cognition.

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. The scale of these assays is achievable with the Stellar™ mass spectrometer through the accommodation of shifting retention times by real-time alignment, while being sensitive and fast enough to handle many concurrent targets. Assays were constructed using precursor information from gas-phase fractionated (GPF) data-independent acquisition (DIA). We demonstrate the ability to schedule methods from an orbitrap and linear ion trap acquired GPF DIA library and compare the quantification of a matrix-matched calibration curve from orbitrap DIA and linear ion trap parallel reaction monitoring (PRM). Two applications of these proposed workflows are shown with a cerebrospinal fluid (CSF) neurodegenerative disease protein PRM assay and with a Mag-Net enriched plasma extracellular vesicle (EV) protein survey PRM assay.

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. Internal QCs incorporated at protein and peptide-level allow our team to assess sample preparation issues and to differentiate system failures from sample-specific issues. External QC samples prepared alongside our experimental samples are used to verify the consistency and quantitative potential of our results during batch correction and normalization before assessing biological phenotypes. We combine these controls with rapid analysis (Skyline), longitudinal QC metrics (AutoQC), and server-based data deposition (PanoramaWeb). We propose that this integrated approach to QC is a useful starting point for groups to facilitate rapid quality control assessment to ensure that valuable instrument time is used to collect the best quality data possible. Data are available on Panorama Public and on ProteomeXchange under the identifier PXD051318.

Mouse sarcopenia model reveals sex- and age-specific differences in phenotypic and molecular characteristics.

Our study was to characterize sarcopenia in C57BL/6J mice using a clinically relevant definition to investigate the underlying molecular mechanisms. Aged male (23-32 months old) and female (27-28 months old) C57BL/6J mice were classified as non-, probable-, or sarcopenic based on assessments of grip strength, muscle mass, and treadmill running time, using 2 SDs below the mean of their young counterparts as cutoff points. A 9%-22% prevalence of sarcopenia was identified in 23-26 month-old male mice, with more severe age-related declines in muscle function than mass. Females aged 27-28 months showed fewer sarcopenic but more probable cases compared with the males. As sarcopenia progressed, a decrease in muscle contractility and a trend toward lower type IIB fiber size were observed in males. Mitochondrial biogenesis, oxidative capacity, and AMPK-autophagy signaling decreased as sarcopenia progressed in males, with pathways linked to mitochondrial metabolism positively correlated with muscle mass. No age- or sarcopenia-related changes were observed in mitochondrial biogenesis, OXPHOS complexes, AMPK signaling, mitophagy, or atrogenes in females. Our results highlight the different trajectories of age-related declines in muscle mass and function, providing insights into sex-dependent molecular changes associated with sarcopenia progression, which may inform the future development of novel therapeutic interventions.

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. The Mag-Net method is robust, reproducible, inexpensive, and requires <100 µL plasma input. Coupled to a quantitative data-independent mass spectrometry analytical strategy, we demonstrate that we can collect results for >37,000 peptides from >4,000 plasma proteins with high precision. Using this analytical pipeline on a small cohort of patients with neurodegenerative disease and healthy age-matched controls, we discovered 204 proteins that differentiate (q-value < 0.05) patients with Alzheimer's disease dementia (ADD) from those without ADD. Our method also discovered 310 proteins that were different between Parkinson's disease and those with either ADD or healthy cognitively normal individuals. Using machine learning we were able to distinguish between ADD and not ADD with a mean ROC AUC = 0.98 ± 0.06.

Hippocampus Glutathione S Reductase Potentially Confers Genetic Resilience to Cognitive Decline in the AD-BXD Mouse Population.

Alzheimer's disease (AD) is a prevalent and costly age-related dementia. Heritable factors account for 58-79% of variation in late-onset AD, but substantial variation remains in age-of- onset, disease severity, and whether those with high-risk genotypes acquire AD. To emulate the diversity of human populations, we utilized the AD-BXD mouse panel. This genetically diverse resource combines AD genotypes with multiple BXD strains to discover new genetic drivers of AD resilience. Comparing AD-BXD carriers to noncarrier littermates, we computed a novel quantitative metric for resilience to cognitive decline in the AD-BXDs. Our quantitative AD resilience trait was heritable and genetic mapping identified a locus on chr8 associated with resilience to AD mutations that resulted in amyloid brain pathology. Using a hippocampus proteomics dataset, we nominated the mitochondrial glutathione S reductase protein (GR or GSHR) as a resilience factor, finding that the DBA/2J genotype was associated with substantially higher GR abundance. By mapping protein QTLs (pQTLs), we identified synaptic organization and mitochondrial proteins coregulated in trans with a cis-pQTL for GR. We found four coexpression modules correlated with the quantitative resilience score in aged 5XFAD mice using paracliques, which were related to cell structure, protein folding, and postsynaptic densities. Finally, we found significant positive associations between human GSR transcript abundance in the brain and better outcomes on AD-related cognitive and pathology traits in the Religious Orders Study/Memory and Aging project (ROSMAP). Taken together, these data support a framework for resilience in which neuronal antioxidant pathway activity provides for stability of synapses within the hippocampus.

Unveiling Resilience to Alzheimer's Disease: Insights From Brain Regional Proteomic Markers.

Studying proteomics data of the human brain could offer numerous insights into unraveling the signature of resilience to Alzheimer's disease. In our previous study with rigorous cohort selection criteria that excluded 4 common comorbidities, we harnessed multiple brain regions from 43 research participants with 12 of them displaying cognitive resilience to Alzheimer's disease. Based on the previous findings, this work focuses on 6 proteins out of the 33 differentially expressed proteins associated with resilience to Alzheimer's disease. These proteins are used to construct a decision tree classifier, enabling the differentiation of 3 groups: (i) healthy control, (ii) resilience to Alzheimer's disease, and (iii) Alzheimer's disease with dementia. Our analysis unveiled 2 important regional proteomic markers: Aß peptides in the hippocampus and PA1B3 in the inferior parietal lobule. These findings underscore the potential of using distinct regional proteomic markers as signatures in characterizing the resilience to Alzheimer's disease.

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 Aß levels is a significant feature of resilience when compared to healthy control and Alzheimer's disease dementia groups. Protein co-expression analysis reveals 181 densely-interacting proteins significantly associated with resilience that were enriched for actin filament-based processes, cellular detoxification, and wound healing in isocortex and hippocampus, further supported by four validation cohorts. Our results suggest that lowering soluble Aß concentration may suppress severe cognitive impairment along the Alzheimer's disease continuum. The molecular basis of resilience likely holds important therapeutic insights.

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. To better understand the molecular signatures of disease we constructed a unique human brain sample cohort inclusive of autosomal dominant AD dementia (ADD), sporadic ADD, and those without dementia but with high AD histopathologic burden, and cognitively normal individuals with no/minimal AD histopathologic burden. All samples are clinically well characterized, and brain tissue was preserved postmortem by rapid autopsy. Samples from four brain regions were processed and analyzed by data-independent acquisition LC-MS/MS. Here we present a high-quality quantitative dataset at the peptide and protein level for each brain region. Multiple internal and external control strategies were included in this experiment to ensure data quality. All data are deposited in the ProteomeXchange repositories and available from each step of our processing.