Explore the vast range of titles available.

Mammalian cells have about 30,000 times as many protein molecules as mRNA molecules, which has major implications in the development of proteomics technologies. We discuss strategies that have been helpful for counting billions of protein molecules by liquid chromatography–tandem mass spectrometry and suggest that these strategies can benefit single-molecule methods, especially in mitigating the challenges posed by the wide dynamic range of the proteome.

Data independent acquisition (DIA) mass spectrometry is a powerful technique that is improving the reproducibility and throughput of proteomics studies. Here, we introduce an experimental workflow that uses this technique to construct chromatogram libraries that capture fragment ion chromatographic peak shape and retention time for every detectable peptide in a proteomics experiment. These coordinates calibrate protein databases or spectrum libraries to a specific mass spectrometer and chromatography setup, facilitating DIA-only pipelines and the reuse of global resource libraries. We also present EncyclopeDIA, a software tool for generating and searching chromatogram libraries, and demonstrate the performance of our workflow by quantifying proteins in human and yeast cells. We find that by exploiting calibrated retention time and fragmentation specificity in chromatogram libraries, EncyclopeDIA can detect 20–25% more peptides from DIA experiments than with data dependent acquisition-based spectrum libraries alone. Data-independent acquisition (DIA)-based proteomics often relies on mass spectrum libraries from data-dependent acquisition experiments. Here, the authors present a method to generate DIA-based chromatogram libraries, enabling DIA-only workflows and detecting more peptides than with spectrum libraries alone.

Huanglongbing, or citrus greening disease, is an economically devastating bacterial disease of citrus. It is associated with infection by the gram-negative bacterium Candidatus Liberibacter asiaticus (CLas). CLas is transmitted by Diaphorina citri, the Asian citrus psyllid (ACP). For insect transmission to occur, CLas must be ingested during feeding on infected phloem sap and cross the gut barrier to gain entry into the insect vector. To investigate the effects of CLas exposure at the gut-pathogen interface, we performed RNAseq and mass spectrometry-based proteomics to analyze the transcriptome and proteome, respectively, of ACP gut tissue. CLas exposure resulted in changes in pathways involving the TCA cycle, iron metabolism, insecticide resistance and the insect's immune system. We identified 83 long non-coding RNAs that are responsive to CLas, two of which appear to be specific to the ACP. Proteomics analysis also enabled us to determine that Wolbachia, a symbiont of the ACP, undergoes proteome regulation when CLas is present. Fluorescent in situ hybridization (FISH) confirmed that Wolbachia and CLas inhabit the same ACP gut cells, but do not co-localize within those cells. Wolbachia cells are prevalent throughout the gut epithelial cell cytoplasm, and Wolbachia titer is more variable in the guts of CLas exposed insects. CLas is detected on the luminal membrane, in puncta within the gut epithelial cell cytoplasm, along actin filaments in the gut visceral muscles, and rarely, in association with gut cell nuclei. Our study provides a snapshot of how the psyllid gut copes with CLas exposure and provides information on pathways and proteins for targeted disruption of CLas-vector interactions at the gut interface.

Diastolic dysfunction is a prominent feature of cardiac aging in both mice and humans. We show here that 8-week treatment of old mice with the mitochondrial targeted peptide SS-31 (elamipretide) can substantially reverse this deficit. SS-31 normalized the increase in proton leak and reduced mitochondrial ROS in cardiomyocytes from old mice, accompanied by reduced protein oxidation and a shift towards a more reduced protein thiol redox state in old hearts. Improved diastolic function was concordant with increased phosphorylation of cMyBP-C Ser282 but was independent of titin isoform shift. Late-life viral expression of mitochondrial-targeted catalase (mCAT) produced similar functional benefits in old mice and SS-31 did not improve cardiac function of old mCAT mice, implicating normalizing mitochondrial oxidative stress as an overlapping mechanism. These results demonstrate that pre-existing cardiac aging phenotypes can be reversed by targeting mitochondrial dysfunction and implicate mitochondrial energetics and redox signaling as therapeutic targets for cardiac aging.

Many peptide hormones form an α-helix on binding their receptors 1 – 4 , and sensitive methods for their detection could contribute to better clinical management of disease 5 . De novo protein design can now generate binders with high affinity and specificity to structured proteins 6 , 7 . However, the design of interactions between proteins and short peptides with helical propensity is an unmet challenge. Here we describe parametric generation and deep learning-based methods for designing proteins to address this challenge. We show that by extending RFdiffusion 8 to enable binder design to flexible targets, and to refining input structure models by successive noising and denoising (partial diffusion), picomolar-affinity binders can be generated to helical peptide targets by either refining designs generated with other methods, or completely de novo starting from random noise distributions without any subsequent experimental optimization. The RFdiffusion designs enable the enrichment and subsequent detection of parathyroid hormone and glucagon by mass spectrometry, and the construction of bioluminescence-based protein biosensors. The ability to design binders to conformationally variable targets, and to optimize by partial diffusion both natural and designed proteins, should be broadly useful. A study describes a direct computational approach without experimental optimization to design high-affinity proteins that bind small helical peptides.

Photoperiod is one of the most reliable environmental cues for plants to regulate flowering timing. In Arabidopsis thaliana, CONSTANS (CO) transcription factor plays a central role in regulating photoperiodic flowering. In contrast to posttranslational regulation of CO protein, still little was known about CO transcriptional regulation. Here we show that the CINCINNATA (CIN) clade of class II TEOSINTE BRANCHED 1/ CYCLOIDEA/ PROLIFERATING CELL NUCLEAR ANTIGEN FACTOR (TCP) proteins act as CO activators. Our yeast one-hybrid analysis revealed that class II CIN-TCPs, including TCP4, bind to the CO promoter. TCP4 induces CO expression around dusk by directly associating with the CO promoter in vivo. In addition, TCP4 binds to another flowering regulator, GIGANTEA (GI), in the nucleus, and induces CO expression in a GI-dependent manner. The physical association of TCP4 with the CO promoter was reduced in the gi mutant, suggesting that GI may enhance the DNA-binding ability of TCP4. Our tandem affinity purification coupled with mass spectrometry (TAP-MS) analysis identified all class II CIN-TCPs as the components of the in vivo TCP4 complex, and the gi mutant did not alter the composition of the TCP4 complex. Taken together, our results demonstrate a novel function of CIN-TCPs as photoperiodic flowering regulators, which may contribute to coordinating plant development with flowering regulation.

A library-free, peptide-centric search tool, PECAN, robustly identifies peptides from data-independent acquisition mass-spectrometry-based proteomics data. Data-independent acquisition (DIA) is an emerging mass spectrometry (MS)-based technique for unbiased and reproducible measurement of protein mixtures. DIA tandem mass spectrometry spectra are often highly multiplexed, containing product ions from multiple cofragmenting precursors. Detecting peptides directly from DIA data is therefore challenging; most DIA data analyses require spectral libraries. Here we present PECAN ( http://pecan.maccosslab.org ), a library-free, peptide-centric tool that robustly and accurately detects peptides directly from DIA data. PECAN reports evidence of detection based on product ion scoring, which enables detection of low-abundance analytes with poor precursor ion signal. We demonstrate the chromatographic peak picking accuracy and peptide detection capability of PECAN, and we further validate its detection with data-dependent acquisition and targeted analyses. Lastly, we used PECAN to build a plasma proteome library from DIA data and to query known sequence variants.

The accumulation of damaged mitochondria has been proposed as a key factor in aging and the pathogenesis of many common agerelated 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 autophagydeficient 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.

Analyzing proteins from single cells by tandem mass spectrometry (MS) has recently become technically feasible. While such analysis has the potential to accurately quantify thousands of proteins across thousands of single cells, the accuracy and reproducibility of the results may be undermined by numerous factors affecting experimental design, sample preparation, data acquisition and data analysis. We expect that broadly accepted community guidelines and standardized metrics will enhance rigor, data quality and alignment between laboratories. Here we propose best practices, quality controls and data-reporting recommendations to assist in the broad adoption of reliable quantitative workflows for single-cell proteomics. Resources and discussion forums are available at https://single-cell.net/guidelines . A community of researchers working in the emerging field of single-cell proteomics propose best-practice experimental and computational recommendations and reporting guidelines for studies analyzing proteins from single cells by mass spectrometry.

A major goal of proteomics research is the accurate and sensitive identification and quantification of a broad range of proteins within a sample. Data-independent acquisition (DIA) approaches that acquire MS/MS spectra independently of precursor information have been developed to overcome the reproducibility challenges of data-dependent acquisition and the limited breadth of targeted proteomics strategies. Typical DIA implementations use wide MS/MS isolation windows to acquire comprehensive fragment ion data. However, wide isolation windows produce highly chimeric spectra, limiting the achievable sensitivity and accuracy of quantification and identification. Here, we present a DIA strategy in which spectra are collected with overlapping (rather than adjacent or random) windows and then computationally demultiplexed. This approach improves precursor selectivity by nearly a factor of 2, without incurring any loss in mass range, mass resolution, chromatographic resolution, scan speed, or other key acquisition parameters. We demonstrate a 64% improvement in sensitivity and a 17% improvement in peptides detected in a 6-protein bovine mix spiked into a yeast background. To confirm the method’s applicability to a realistic biological experiment, we also analyze the regulation of the proteasome in yeast grown in rapamycin and show that DIA experiments with overlapping windows can help elucidate its adaptation toward the degradation of oxidatively damaged proteins. Our integrated computational and experimental DIA strategy is compatible with any DIA-capable instrument. The computational demultiplexing algorithm required to analyze the data has been made available as part of the open-source proteomics software tools Skyline and msconvert (Proteowizard), making it easy to apply as part of standard proteomics workflows.Graphical Abstractᅟ