Preparing Better Samples for Cryo-Electron Microscopy: Biochemical Challenges Do Not End with Isolation and Purification.

The preparation of extremely thin samples, which are required for high-resolution electron microscopy, poses extreme risk of damaging biological macromolecules due to interactions with the air-water interface. Although the rapid increase in the number of published structures initially gave little indication that this was a problem, the search for methods that substantially mitigate this hazard is now intensifying. The two main approaches under investigation are (a) immobilizing particles onto structure-friendly support films and (b) reducing the length of time during which such interactions may occur. While there is little possibility of outrunning diffusion to the interface, intentional passivation of the interface may slow the process of adsorption and denaturation. In addition, growing attention is being given to gaining more effective control of the thickness of the sample prior to vitrification.

The integral role of de novo lipogenesis in the preparation for seasonal dormancy.

Animals can alter their body compositions in anticipation of dormancy to endure seasons with limited food availability. Accumulation of lipid reserves, mostly in the form of triglycerides (TAGs), is observed during the preparation for dormancy in diverse animals, including insects (diapause) and mammals (hibernation). However, the mechanisms involved in the regulation of lipid accumulation and the ecological consequences of failure to accumulate adequate lipid stores in preparation for animal dormancy remain understudied. In the broadest sense, lipid reserves can be accumulated in two ways: the animal either receives lipids directly from the environment or converts the sugars and amino acids present in food to fatty acids through de novo lipogenesis and then to TAGs. Here, we show that preparation for diapause in the Colorado potato beetle (Leptinotarsa decemlineata) involves orchestrated upregulation of genes involved in lipid metabolism with a transcript peak in 8- and 10-d-old diapause-destined insects. Regulation at the transcript abundance level was associated with the accumulation of substantial fat stores. Furthermore, the knockdown of de novo lipogenesis enzymes (ACCase and FAS-1) prolonged the preparatory phase, while the knockdown of fatty acid transportation genes shortened the preparatory phase. Our findings suggest a model in which the insects dynamically decide when to transition from the preparation phase into diapause, depending on the progress in lipid accumulation through de novo lipogenesis.

Graphene sandwich-based biological specimen preparation for cryo-EM analysis.

High-quality specimen preparation plays a crucial role in cryo-electron microscopy (cryo-EM) structural analysis. In this study, we have developed a reliable and convenient technique called the graphene sandwich method for preparing cryo-EM specimens. This method involves using two layers of graphene films that enclose macromolecules on both sides, allowing for an appropriate ice thickness for cryo-EM analysis. The graphene sandwich helps to mitigate beam-induced charging effect and reduce particle motion compared to specimens prepared using the traditional method with graphene support on only one side, therefore improving the cryo-EM data quality. These advancements may open new opportunities to expand the use of graphene in the field of biological electron microscopy.

Current concepts, advances, and challenges in deciphering the human microbiota with metatranscriptomics.

Metatranscriptomics refers to the analysis of the collective microbial transcriptome of a sample. Its increased utilization for the characterization of human-associated microbial communities has enabled the discovery of many disease-state related microbial activities. Here, we review the principles of metatranscriptomics-based analysis of human-associated microbial samples. We describe strengths and weaknesses of popular sample preparation, sequencing, and bioinformatics approaches and summarize strategies for their use. We then discuss how human-associated microbial communities have recently been examined and how their characterization may change. We conclude that metatranscriptomics insights into human microbiotas under health and disease have not only expanded our knowledge on human health, but also opened avenues for rational antimicrobial drug use and disease management.

An initial game-theoretic assessment of enhanced tissue preparation and imaging protocols for improved deep learning inference of spatial transcriptomics from tissue morphology.

The application of deep learning to spatial transcriptomics (ST) can reveal relationships between gene expression and tissue architecture. Prior work has demonstrated that inferring gene expression from tissue histomorphology can discern these spatial molecular markers to enable population scale studies, reducing the fiscal barriers associated with large-scale spatial profiling. However, while most improvements in algorithmic performance have focused on improving model architectures, little is known about how the quality of tissue preparation and imaging can affect deep learning model training for spatial inference from morphology and its potential for widespread clinical adoption. Prior studies for ST inference from histology typically utilize manually stained frozen sections with imaging on non-clinical grade scanners. Training such models on ST cohorts is also costly. We hypothesize that adopting tissue processing and imaging practices that mirror standards for clinical implementation (permanent sections, automated tissue staining, and clinical grade scanning) can significantly improve model performance. An enhanced specimen processing and imaging protocol was developed for deep learning-based ST inference from morphology. This protocol featured the Visium CytAssist assay to permit automated hematoxylin and eosin staining (e.g. Leica Bond), 40×-resolution imaging, and joining of multiple patients' tissue sections per capture area prior to ST profiling. Using a cohort of 13 pathologic T Stage-III stage colorectal cancer patients, we compared the performance of models trained on slide prepared using enhanced versus traditional (i.e. manual staining and low-resolution imaging) protocols. Leveraging Inceptionv3 neural networks, we predicted gene expression across serial, histologically-matched tissue sections using whole slide images (WSI) from both protocols. The data Shapley was used to quantify and compare marginal performance gains on a patient-by-patient basis attributed to using the enhanced protocol versus the actual costs of spatial profiling. Findings indicate that training and validating on WSI acquired through the enhanced protocol as opposed to the traditional method resulted in improved performance at lower fiscal cost. In the realm of ST, the enhancement of deep learning architectures frequently captures the spotlight; however, the significance of specimen processing and imaging is often understated. This research, informed through a game-theoretic lens, underscores the substantial impact that specimen preparation/imaging can have on spatial transcriptomic inference from morphology. It is essential to integrate such optimized processing protocols to facilitate the identification of prognostic markers at a larger scale.

ZASP: A Highly Compatible and Sensitive ZnCl2 Precipitation-Assisted Sample Preparation Method for Proteomic Analysis.

Universal sample preparation for proteomic analysis that enables unbiased protein manipulation, flexible reagent use, and low protein loss is required to ensure the highest sensitivity of downstream liquid chromatography-mass spectrometry (LC-MS) analysis. To address these needs, we developed a ZnCl2 precipitation-assisted sample preparation method (ZASP) that depletes harsh detergents and impurities in protein solutions prior to trypsin digestion via 10 min of ZnCl2 and methanol-induced protein precipitation at room temperature (RT). ZASP can remove trypsin digestion and LC-MS incompatible detergents such as SDS, Triton X-100, and urea at high concentrations in solution and unbiasedly recover proteins independent of the amount of protein input. We demonstrated the sensitivity and reproducibility of ZASP in an analysis of samples with 1 µg to 1000 µg of proteins. Compared to commonly used sample preparation methods such as SDC-based in-solution digestion, acetone precipitation, FASP, and SP3, ZASP has proven to be an efficient approach. Here, we present ZASP, a practical, robust, and cost-effective proteomic sample preparation method that can be applied to profile different types of samples.

Differential Formation of Motor Cortical Dynamics during Movement Preparation According to the Predictability of Go Timing.

The motor cortex not only executes but also prepares movement, as motor cortical neurons exhibit preparatory activity that predicts upcoming movements. In movement preparation, animals adopt different strategies in response to uncertainties existing in nature such as the unknown timing of when a predator will attack-an environmental cue informing "go." However, how motor cortical neurons cope with such uncertainties is less understood. In this study, we aim to investigate whether and how preparatory activity is altered depending on the predictability of "go" timing. We analyze firing activities of the anterior lateral motor cortex in male mice during two auditory delayed-response tasks each with predictable or unpredictable go timing. When go timing is unpredictable, preparatory activities immediately reach and stay in a neural state capable of producing movement anytime to a sudden go cue. When go timing is predictable, preparation activity reaches the movement-producible state more gradually, to secure more accurate decisions. Surprisingly, this preparation process entails a longer reaction time. We find that as preparatory activity increases in accuracy, it takes longer for a neural state to transition from the end of preparation to the start of movement. Our results suggest that the motor cortex fine-tunes preparatory activity for more accurate movement using the predictability of go timing.

µPhos: a scalable and sensitive platform for high-dimensional phosphoproteomics.

Mass spectrometry has revolutionized cell signaling research by vastly simplifying the analysis of many thousands of phosphorylation sites in the human proteome. Defining the cellular response to perturbations is crucial for further illuminating the functionality of the phosphoproteome. Here we describe µPhos ('microPhos'), an accessible phosphoproteomics platform that permits phosphopeptide enrichment from 96-well cell culture and small tissue amounts in <8 h total processing time. By greatly minimizing transfer steps and liquid volumes, we demonstrate increased sensitivity, >90% selectivity, and excellent quantitative reproducibility. Employing highly sensitive trapped ion mobility mass spectrometry, we quantify ~17,000 Class I phosphosites in a human cancer cell line using 20 µg starting material, and confidently localize ~6200 phosphosites from 1 µg. This depth covers key signaling pathways, rendering sample-limited applications and perturbation experiments with hundreds of samples viable. We employ µPhos to study drug- and time-dependent response signatures in a leukemia cell line, and by quantifying 30,000 Class I phosphosites in the mouse brain we reveal distinct spatial kinase activities in subregions of the hippocampal formation.

An Automated Nanowell-Array Workflow for Quantitative Multiplexed Single-Cell Proteomics Sample Preparation at High Sensitivity.

Multiplexed and label-free mass spectrometry-based approaches with single-cell resolution have attributed surprising heterogeneity to presumed homogenous cell populations. Even though specialized experimental designs and instrumentation have demonstrated remarkable advances, the efficient sample preparation of single cells still lags. Here, we introduce the proteoCHIP, a universal option for single-cell proteomics sample preparation including multiplexed labeling up to 16-plex with high sensitivity and throughput. The automated processing using a commercial system combining single-cell isolation and picoliter dispensing, the cellenONE, reduces final sample volumes to low nanoliters submerged in a hexadecane layer simultaneously eliminating error-prone manual sample handling and overcoming evaporation. The specialized proteoCHIP design allows direct injection of single cells via a standard autosampler resulting in around 1500 protein groups per TMT10-plex with reduced or eliminated need for a carrier proteome. We evaluated the effect of wider precursor isolation windows at single-cell input levels and found that using 2 Da isolation windows increased overall sensitivity without significantly impacting interference. Using the dedicated mass spectrometry acquisition strategies detailed here, we identified on average close to 2000 proteins per TMT10-plex across 170 multiplexed single cells that readily distinguished human cell types. Overall, our workflow combines highly efficient sample preparation, chromatographic and ion mobility-based filtering, rapid wide-window data-dependent acquisition analysis, and intelligent data analysis for optimal multiplexed single-cell proteomics. This versatile and automated proteoCHIP-based sample preparation approach is sufficiently sensitive to drive biological applications of single-cell proteomics and can be readily adopted by proteomics laboratories.

Preparing Patients for Oral Immunotherapy (PPOINT): International Delphi consensus for procedural preparation and consent.

BACKGROUND: Despite the promise of oral immunotherapy (OIT) to treat food allergies, this procedure is associated with potential risk. There is no current agreement about what elements should be included in the preparatory or consent process. OBJECTIVE: We developed consensus recommendations about the OIT process considerations and patient-specific factors that should be addressed before initiating OIT and developed a consensus OIT consent process and information form. METHODS: We convened a 36-member Preparing Patients for Oral Immunotherapy (PPOINT) panel of allergy experts to develop a consensus OIT patient preparation, informed consent process, and framework form. Consensus for themes and statements was reached using Delphi methodology, and the consent information form was developed. RESULTS: The expert panel reached consensus for 4 themes and 103 statements specific to OIT preparatory procedures, of which 76 statements reached consensus for inclusion specific to the following themes: general considerations for counseling patients about OIT; patient- and family-specific factors that should be addressed before initiating OIT and during OIT; indications for initiating OIT; and potential contraindications and precautions for OIT. The panel reached consensus on 9 OIT consent form themes: benefits, risks, outcomes, alternatives, risk mitigation, difficulties/challenges, discontinuation, office policies, and long-term management. From these themes, 219 statements were proposed, of which 189 reached consensus, and 71 were included on the consent information form. CONCLUSION: We developed consensus recommendations to prepare and counsel patients for safe and effective OIT in clinical practice with evidence-based risk mitigation. Adoption of these recommendations may help standardize clinical care and improve patient outcomes and quality of life.

Matrix-Free Thermally Activated Delayed Fluorescent Carbon Dots-Based Electroluminescent Light-Emitting Diodes Exceeding 5.6% External Quantum Efficiency.

Carbon dots (CDs) are promising luminescent emission layer materials for next generation electroluminescent light emitting diodes (EL-LEDs) due to their many advantages, such as environmental friendliness, low cost, and high stability. However, limited by the spin-forbidden properties of the triplet transition, it is difficult to improve the external quantum efficiency (EQE) of fluorescent CDs-based EL-LEDs. Meanwhile, traditional thermally activated delayed fluorescent (TADF) CDs prepared using coating strategies are difficult to utilize in EL-LEDs due to the nonconductivity of the coating agent. Herein, we successfully developed matrix-free TADF CDs with yellow emission and achieved a device EQE of 5.68%, which is the highest value reported in CDs-based EL-LEDs. In addition, we also developed white EL-LEDs with an EQE of 1.70%. This study highlights the importance of interactions between precursors in modulating the electroluminescence properties of TADF emitters and provides an effective design principle for matrix-free TADF CDs.

Scalable Multistep Imprinting of Multiplexed Optical Anti-counterfeiting Patterns with Hierarchical Structures.

Multiplexed optical techniques with multichannel patterns provide powerful strategies for high-capacity anti-counterfeiting. However, it is still a big challenge to meet the demands of achieving high encryption levels, excellent readability, and simple preparation simultaneously. Herein, we use a multistep imprinting technique, leveraging surface work-hardening to massively produce multiplexed encrypted patterns with hierarchical structures. These patterns with coupled nano- and microstructures can be instantaneously decoded into different pieces of information at different view angles under white light illumination. By incorporating perpendicular nano- and microgratings, we achieve four-channel encoded patterns, enhancing anti-counterfeiting capacity. This versatile method works on various metal/polymer materials, offering high-density information storage, direct visibility, broad material compatibility, and low-cost mass production. Our high-performance anti-counterfeiting patterns show significant potential in real-world applications.

HowDirty: An R package to evaluate molecular contaminants in LC-MS experiments.

Contaminants derived from consumables, reagents, and sample handling often negatively affect LC-MS data acquisition. In proteomics experiments, they can markedly reduce identification performance, reproducibility, and quantitative robustness. Here, we introduce a data analysis workflow combining MS1 feature extraction in Skyline with HowDirty, an R-markdown-based tool, that automatically generates an interactive report on the molecular contaminant level in LC-MS data sets. To facilitate the interpretation of the results, the HTML report is self-contained and self-explanatory, including plots that can be easily interpreted. The R package HowDirty is available from https://github.com/DavidGZ1/HowDirty. To demonstrate a showcase scenario for the application of HowDirty, we assessed the impact of ultrafiltration units from different providers on sample purity after filter-assisted sample preparation (FASP) digestion. This allowed us to select the filter units with the lowest contamination risk. Notably, the filter units with the lowest contaminant levels showed higher reproducibility regarding the number of peptides and proteins identified. Overall, HowDirty enables the efficient evaluation of sample quality covering a wide range of common contaminant groups that typically impair LC-MS analyses, facilitating corrective or preventive actions to minimize instrument downtime.

Assessing the precision of a detergent-assisted cartridge precipitation workflow for non-targeted quantitative proteomics.

Detergent-based workflows incorporating sodium dodecyl sulfate (SDS) necessitate additional steps for detergent removal ahead of mass spectrometry (MS). These steps may lead to variable protein recovery, inconsistent enzyme digestion efficiency, and unreliable MS signals. To validate a detergent-based workflow for quantitative proteomics, we herein evaluate the precision of a bottom-up sample preparation strategy incorporating cartridge-based protein precipitation with organic solvent to deplete SDS. The variance of data-independent acquisition (SWATH-MS) data was isolated from sample preparation error by modelling the variance as a function of peptide signal intensity. Our SDS-assisted cartridge workflow yield a coefficient of variance (CV) of 13%-14%. By comparison, conventional (detergent-free) in-solution digestion increased the CV to 50%; in-gel digestion provided lower CVs between 14% and 20%. By filtering peptides predicting to display lower precision, we further enhance the validity of data in global comparative proteomics. These results demonstrate the detergent-based precipitation workflow is a reliable approach for in depth, label-free quantitative proteome analysis.

Proactive Interhemispheric Disinhibition Supports Response Preparation during Selective Stopping.

Response inhibition is essential for terminating inappropriate actions. A substantial response delay may occur in the nonstopped effector when only part of a multieffector action is terminated. This stopping-interference effect has been attributed to nonselective response inhibition processes and can be reduced with proactive cuing. This study aimed to elucidate the role of interhemispheric primary motor cortex (M1-M1) influences during selective stopping with proactive cuing. We hypothesized that stopping-interference would be reduced as stopping certainty increased because of proactive recruitment of interhemispheric facilitation or inhibition when cued to respond or stop, respectively. Twenty-three healthy human participants of either sex performed a bimanual anticipatory response inhibition paradigm with cues signaling the likelihood of a stop-signal occurring. Dual-coil transcranial magnetic stimulation was used to determine corticomotor excitability (CME), interhemispheric inhibition (IHI), and interhemispheric facilitation (IHF) in the left hand at rest and during response preparation. Response times slowed and stopping-interference decreased with increased stopping certainty. Proactive response inhibition was marked by a reduced rate of rise and faster cancel time in electromyographical bursts during stopping. There was a nonselective release of IHI but not CME from rest to in-task response preparation, whereas IHF was not observed in either context. An effector-specific reduction in CME but no reinstatement of IHI was observed when the left hand was cued to stop. These findings indicate that stopping speed and selectivity are better with proactive cueing and that interhemispheric M1-M1 channels modulate inhibitory tone during response preparation to support going but not proactive response inhibition.SIGNIFICANCE STATEMENT Response inhibition is essential for terminating inappropriate actions and, in some cases, may be required for only part of a multieffector action. The present study examined interhemispheric influences between the primary motor cortices during selective stopping with proactive cuing. Stopping selectivity was greater with increased stopping certainty and was marked by proactive adjustments to the hand cued to stop and hand cued to respond separately. Inhibitory interhemispheric influences were released during response preparation but were not directly involved in proactive response inhibition. These findings indicate that between-hand stopping can be selective with proactive cuing, but cue-related improvements are unlikely to reflect the advance engagement of interhemispheric influences between primary motor cortices.

ChipFilter: Microfluidic-Based Comprehensive Sample Preparation Methodology for Microbial Consortia.

The metaproteomic approach is an attractive way to describe a microbiome at the functional level, allowing the identification and quantification of proteins across a broad dynamic range as well as the detection of post-translational modifications. However, it remains relatively underutilized, mainly due to technical challenges that should be addressed, including the complexity of extracting proteins from heterogeneous microbial communities. Here, we show that a ChipFilter microfluidic device coupled to a liquid chromatography tandem mass spectrometry (LC-MS/MS) setup can be successfully used for the identification of microbial proteins. Using cultures of Escherichia coli, Bacillus subtilis, and Saccharomyces cerevisiae, we have shown that it is possible to directly lyse the cells and digest the proteins in the ChipFilter to allow the identification of a higher number of proteins and peptides than that by standard protocols, even at low cell density. The peptides produced are overall longer after ChipFilter digestion but show no change in their degree of hydrophobicity. Analysis of a more complex mixture of 17 species from the gut microbiome showed that the ChipFilter preparation was able to identify and estimate the amounts of 16 of these species. These results show that ChipFilter can be used for the proteomic study of microbiomes, particularly in the case of a low volume or cell density. The mass spectrometry data have been deposited on the ProteomeXchange Consortium via the PRIDE partner repository with the data set identifier PXD039581.

Differences in Protein Capture by SP3 and SP4 Demonstrate Mechanistic Insights of Proteomics Cleanup Techniques.

The goal of proteomics experiments is to identify proteins to observe changes in cellular processes and diseases. One challenge in proteomics is the removal of contaminants following protein extraction, which can limit protein identifications. Single-pot, solid-phase-enhanced sample preparation (SP3) is a cleanup technique in which proteins are captured on carboxylate-modified particles through a proposed hydrophilic-interaction-liquid-chromatography (HILIC)-like mechanism. Recent results have suggested that proteins are captured in SP3 due to a protein-aggregation mechanism. Solvent precipitation, single-pot, solid-phase-enhanced sample preparation (SP4) is a newer cleanup technique that employs protein aggregation to capture proteins without modified particles. We hypothesize that differences in capture mechanisms of SP3 and SP4 affect which proteins are identified by each cleanup technique. Herein, we assess the proteins identified and enriched using SP3 versus SP4 for MCF7 subcellular fractions and correlate protein capture in each method to protein hydrophobicity. Our results indicate that SP3 captures more hydrophilic proteins through a combination of HILIC-like and protein-aggregation mechanisms, while SP4 captures more hydrophobic proteins through a protein-aggregation mechanism. Ultimately, we demonstrate that protein-capture mechanisms are distinct, and the selection of a cleanup technique that yields high proteome coverage is dependent on protein-sample hydrophobicity. Data has been deposited into MassIVE (MSV000094130) and ProteomeXchange (PXD049965).

End-to-End Throughput Chemical Proteomics for Photoaffinity Labeling Target Engagement and Deconvolution.

Photoaffinity labeling (PAL) methodologies have proven to be instrumental for the unbiased deconvolution of protein-ligand binding events in physiologically relevant systems. However, like other chemical proteomic workflows, they are limited in many ways by time-intensive sample manipulations and data acquisition techniques. Here, we describe an approach to address this challenge through the innovation of a carboxylate bead-based protein cleanup procedure to remove excess small-molecule contaminants and couple it to plate-based, proteomic sample processing as a semiautomated solution. The analysis of samples via label-free, data-independent acquisition (DIA) techniques led to significant improvements on a workflow time per sample basis over current standard practices. Experiments utilizing three established PAL ligands with known targets, (+)-JQ-1, lenalidomide, and dasatinib, demonstrated the utility of having the flexibility to design experiments with a myriad of variables. Data revealed that this workflow can enable the confident identification and rank ordering of known and putative targets with outstanding protein signal-to-background enrichment sensitivity. This unified end-to-end throughput strategy for processing and analyzing these complex samples could greatly facilitate efficient drug discovery efforts and open up new opportunities in the chemical proteomics field.

A Rapid One-Pot Workflow for Sensitive Microscale Phosphoproteomics.

Compared to advancements in single-cell proteomics, phosphoproteomics sensitivity has lagged behind due to low abundance, complex sample preparation, and substantial sample input requirements. We present a simple and rapid one-pot phosphoproteomics workflow (SOP-Phos) integrated with data-independent acquisition mass spectrometry (DIA-MS) for microscale phosphoproteomic analysis. SOP-Phos adapts sodium deoxycholate based one-step lysis, reduction/alkylation, direct trypsinization, and phosphopeptide enrichment by TiO2 beads in a single-tube format. By reducing surface adsorptive losses via utilizing n-dodecyl ß-d-maltoside precoated tubes and shortening the digestion time, SOP-Phos is completed within 3-4 h with a 1.4-fold higher identification coverage. SOP-Phos coupled with DIA demonstrated >90% specificity, enhanced sensitivity, lower missing values (<1%), and improved reproducibility (8%-10% CV). With a sample size-comparable spectral library, SOP-Phos-DIA identified 33,787 ± 670 to 22,070 ± 861 phosphopeptides from 5 to 0.5 µg cell lysate and 30,433 ± 284 to 6,548 ± 21 phosphopeptides from 50,000 to 2,500 cells. Such sensitivity enabled mapping key lung cancer signaling sites, such as EGFR autophosphorylation sites Y1197/Y1172 and drug targets. The feasibility of SOP-Phos-DIA was demonstrated on EGFR-TKI sensitive and resistant cells, revealing the interplay of multipathway Hippo-EGFR-ERBB signaling cascades underlying the mechanistic insight into EGFR-TKI resistance. Overall, SOP-Phos-DIA is an efficient and robust protocol that can be easily adapted in the community for microscale phosphoproteomic analysis.

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.