Proteogenomic Analysis of Human Colon Cancer Reveals New Therapeutic Opportunities.

We performed the first proteogenomic study on a prospectively collected colon cancer cohort. Comparative proteomic and phosphoproteomic analysis of paired tumor and normal adjacent tissues produced a catalog of colon cancer-associated proteins and phosphosites, including known and putative new biomarkers, drug targets, and cancer/testis antigens. Proteogenomic integration not only prioritized genomically inferred targets, such as copy-number drivers and mutation-derived neoantigens, but also yielded novel findings. Phosphoproteomics data associated Rb phosphorylation with increased proliferation and decreased apoptosis in colon cancer, which explains why this classical tumor suppressor is amplified in colon tumors and suggests a rationale for targeting Rb phosphorylation in colon cancer. Proteomics identified an association between decreased CD8 T cell infiltration and increased glycolysis in microsatellite instability-high (MSI-H) tumors, suggesting glycolysis as a potential target to overcome the resistance of MSI-H tumors to immune checkpoint blockade. Proteogenomics presents new avenues for biological discoveries and therapeutic development.

Integrated Proteogenomic Characterization of Human High-Grade Serous Ovarian Cancer.

To provide a detailed analysis of the molecular components and underlying mechanisms associated with ovarian cancer, we performed a comprehensive mass-spectrometry-based proteomic characterization of 174 ovarian tumors previously analyzed by The Cancer Genome Atlas (TCGA), of which 169 were high-grade serous carcinomas (HGSCs). Integrating our proteomic measurements with the genomic data yielded a number of insights into disease, such as how different copy-number alternations influence the proteome, the proteins associated with chromosomal instability, the sets of signaling pathways that diverse genome rearrangements converge on, and the ones most associated with short overall survival. Specific protein acetylations associated with homologous recombination deficiency suggest a potential means for stratifying patients for therapy. In addition to providing a valuable resource, these findings provide a view of how the somatic genome drives the cancer proteome and associations between protein and post-translational modification levels and clinical outcomes in HGSC. VIDEO ABSTRACT.

Computational tools and algorithms for ion mobility spectrometry-mass spectrometry.

Ion mobility spectrometry-mass spectrometry (IMS-MS or IM-MS) is a powerful analytical technique that combines the gas-phase separation capabilities of IM with the identification and quantification capabilities of MS. IM-MS can differentiate molecules with indistinguishable masses but different structures (e.g., isomers, isobars, molecular classes, and contaminant ions). The importance of this analytical technique is reflected by a staged increase in the number of applications for molecular characterization across a variety of fields, from different MS-based omics (proteomics, metabolomics, lipidomics, etc.) to the structural characterization of glycans, organic matter, proteins, and macromolecular complexes. With the increasing application of IM-MS there is a pressing need for effective and accessible computational tools. This article presents an overview of the most recent free and open-source software tools specifically tailored for the analysis and interpretation of data derived from IM-MS instrumentation. This review enumerates these tools and outlines their main algorithmic approaches, while highlighting representative applications across different fields. Finally, a discussion of current limitations and expectable improvements is presented.

Deciphering ApoE Genotype-Driven Proteomic and Lipidomic Alterations in Alzheimer's Disease Across Distinct Brain Regions.

Alzheimer's disease (AD) is a neurodegenerative disease with a complex etiology influenced by confounding factors such as genetic polymorphisms, age, sex, and race. Traditionally, AD research has not prioritized these influences, resulting in dramatically skewed cohorts such as three times the number of Apolipoprotein E (APOE) ε4-allele carriers in AD relative to healthy cohorts. Thus, the resulting molecular changes in AD have previously been complicated by the influence of apolipoprotein E disparities. To explore how apolipoprotein E polymorphism influences AD progression, 62 post-mortem patients consisting of 33 AD and 29 controls (Ctrl) were studied to balance the number of ε4-allele carriers and facilitate a molecular comparison of the apolipoprotein E genotype. Lipid and protein perturbations were assessed across AD diagnosed brains compared to Ctrl brains, ε4 allele carriers (APOE4+ for those carrying 1 or 2 ε4s and APOE4- for non-ε4 carriers), and differences in ε3ε3 and ε3ε4 Ctrl brains across two brain regions (frontal cortex (FCX) and cerebellum (CBM)). The region-specific influences of apolipoprotein E on AD mechanisms showcased mitochondrial dysfunction and cell proteostasis at the core of AD pathophysiology in the post-mortem brains, indicating these two processes may be influenced by genotypic differences and brain morphology.

Proteogenomic characterization of difficult-to-treat breast cancer with tumor cells enriched through laser microdissection.

BACKGROUND: Breast cancer (BC) is the most commonly diagnosed cancer and the leading cause of cancer death among women globally. Despite advances, there is considerable variation in clinical outcomes for patients with non-luminal A tumors, classified as difficult-to-treat breast cancers (DTBC). This study aims to delineate the proteogenomic landscape of DTBC tumors compared to luminal A (LumA) tumors. METHODS: We retrospectively collected a total of 117 untreated primary breast tumor specimens, focusing on DTBC subtypes. Breast tumors were processed by laser microdissection (LMD) to enrich tumor cells. DNA, RNA, and protein were simultaneously extracted from each tumor preparation, followed by whole genome sequencing, paired-end RNA sequencing, global proteomics and phosphoproteomics. Differential feature analysis, pathway analysis and survival analysis were performed to better understand DTBC and investigate biomarkers. RESULTS: We observed distinct variations in gene mutations, structural variations, and chromosomal alterations between DTBC and LumA breast tumors. DTBC tumors predominantly had more mutations in TP53, PLXNB3, Zinc finger genes, and fewer mutations in SDC2, CDH1, PIK3CA, SVIL, and PTEN. Notably, Cytoband 1q21, which contains numerous cell proliferation-related genes, was significantly amplified in the DTBC tumors. LMD successfully minimized stromal components and increased RNA-protein concordance, as evidenced by stromal score comparisons and proteomic analysis. Distinct DTBC and LumA-enriched clusters were observed by proteomic and phosphoproteomic clustering analysis, some with survival differences. Phosphoproteomics identified two distinct phosphoproteomic profiles for high relapse-risk and low relapse-risk basal-like tumors, involving several genes known to be associated with breast cancer oncogenesis and progression, including KIAA1522, DCK, FOXO3, MYO9B, ARID1A, EPRS, ZC3HAV1, and RBM14. Lastly, an integrated pathway analysis of multi-omics data highlighted a robust enrichment of proliferation pathways in DTBC tumors. CONCLUSIONS: This study provides an integrated proteogenomic characterization of DTBC vs LumA with tumor cells enriched through laser microdissection. We identified many common features of DTBC tumors and the phosphopeptides that could serve as potential biomarkers for high/low relapse-risk basal-like BC and possibly guide treatment selections.

Mobility Selective Ion Soft-Landing and Characterization Enabled Using Structures for Lossless Ion Manipulation.

While conventional ion-soft landing uses the mass-to-charge (m/z) ratio to achieve molecular selection for deposition, here we demonstrate the use of Structures for Lossless Ion Manipulation (SLIM) for mobility-based ion selection and deposition. The dynamic rerouting capabilities of SLIM were leveraged to enable the rerouting of a selected range of mobilities to a different SLIM path (rather than MS) that terminated at a deposition surface. A selected mobility range from a phosphazene ion mixture was rerouted and deposited with a current pulse (∼150 pA) resembling its mobility peak. In addition, from a mixture of tetra-alkyl ammonium (TAA) ions containing chain lengths of C5-C8, selected chains (C6, C7) were collected on a surface, reconstituted into solution-phase, and subsequently analyzed with a SLIM-qToF to obtain an IMS/MS spectrum, confirming the identity of the selected species. Further, this method was used to characterize triply charged tungsten-polyoxometalate anions, PW12O403- (WPOM). The arrival time distribution of the IMS/MS showed multiple peaks associated with the triply charged anion (PW12O403-), of which a selected ATD was deposited and imaged using TEM. Additionally, the identity of the deposited WPOM was ascertained using energy-dispersive (EDS) spectroscopy. Further, we present theory and computations that reveal ion landing energies, the ability to modulate the energies, and deposition spot sizes.

A Multimodal System for Lipid A Structural Analysis from a Single Colony.

Structural elucidation of Gram-negative bacterial lipid A traditionally requires chemical extraction followed by tandem MS data in the negative ion mode. Previously, we reported FLAT and FLATn as methods to rapidly determine the structure of lipid A without chromatographic techniques. In this work, we extend the capability and effectiveness of these techniques to elucidate the chemical structure in a de novo manner by including the use of positive ion mode (FLAT+ and FLATn+) spectral approaches. Advantages of positive mode analysis of lipid A include the generation of more interpretable and informative fragmentation patterns that include the identification of diagnostic fragments, including selective dissociation of a glycosidic bond between two glucosamine units and the selective dissociation at the secondary acyl chain in 2'-N, allowing for the determination of the composition of fatty acids. As a proof of principle, we present here two previously uncharacterized structures of lipid A from Roseomonas mucosa (R. mucosa) and Moraxella canis (M. canis). In R. mucosa, we determined the lipid A structure with a nonconventional backbone of-ß-1,6 linked 2,3-dideoxy-2,3-diamno-d-glucopyranose further modified with galacturonic acid in the place of typical 1-phosphate, and in M. canis, we assigned a single discrete structure using the specific fragmentation patterns of terminal phosphate groups present in lipid A. Therefore, FLATn+, in combination with FLAT and FLATn, provides a multimodal structural platform for rapid structure characterization of unusual and complex lipid A structures from a single colony.

Comparison of three rapid diagnostic tests for bloodstream infections using Benefit-risk Evaluation Framework (BED-FRAME).

Rapid diagnostic tests (RDTs) for bloodstream infections have the potential to reduce time to appropriate antimicrobial therapy and improve patient outcomes. Previously, an in-house, lipid-based, matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS) method, Fast Lipid Analysis Technique (FLAT MS), has shown promise as a rapid pathogen identification method. In this study, FLAT MS for direct from blood culture identification was evaluated and compared to FDA-cleared identification methods using the Benefit-risk Evaluation Framework (BED-FRAME) analysis. FLAT MS was evaluated and compared to Bruker Sepsityper and bioMérieux BioFire FilmArray BCID2 using results from a previous study. For this study, 301 positive blood cultures were collected from the University of Maryland Medical Center. The RDTs were compared by their sensitivities, time-to-results, hands-on time, and BED-FRAME analysis. The overall sensitivity of all platforms compared to culture results from monomicrobial-positive blood cultures was 88.3%. However, the three RDTs differed in their accuracy for identifying Gram-positive bacteria, Gram-negative bacteria, and yeast. Time-to-results for FLAT MS, Sepsityper, and BioFire BCID2 were all approximately one hour. Hands-on times for FLAT MS, Sepsityper, and BioFire BCID2 were 10 (±1.3), 40 (±2.8), and 5 (±0.25) minutes, respectively. BED-FRAME demonstrated that each RDT had utility at different pathogen prevalence and relative importance. BED-FRAME is a useful tool that can used to determine which RDT is best for a healthcare center.

Identification of a 2-Aminobenzimidazole Scaffold that Potentiates Gram-Positive Selective Antibiotics Against Gram-Negative Bacteria.

The development of novel therapeutic approaches is crucial in the fight against multi-drug resistant (MDR) bacteria, particularly gram-negative species. Small molecule adjuvants that enhance the activity of otherwise gram-positive selective antibiotics against gram-negative bacteria have the potential to expand current treatment options. We have previously reported adjuvants based upon a 2-aminoimidazole (2-AI) scaffold that potentiate macrolide antibiotics against several gram-negative pathogens. Herein, we report the discovery and structure-activity relationship (SAR) investigation of an additional class of macrolide adjuvants based upon a 2-aminobenzimidazole (2-ABI) scaffold. The lead compound lowers the minimum inhibitory concentration (MIC) of clarithromycin (CLR) from 512 to 2 µg/mL at 30 µM against Klebsiella pneumoniae 2146, and from 32 to 2 µg/mL at 5 µM, against Acinetobacter baumannii 5075. Preliminary investigation into the mechanism of action suggests that the compounds are binding to lipopolysaccharide (LPS) in K. pneumoniae, and modulating lipooligosaccharide (LOS) biosynthesis, assembly, or transport in A. baumannii.

Mass spectrometry-based targeted proteomics for analysis of protein mutations.

Cancers are caused by accumulated DNA mutations. This recognition of the central role of mutations in cancer and recent advances in next-generation sequencing, has initiated the massive screening of clinical samples and the identification of 1000s of cancer-associated gene mutations. However, proteomic analysis of the expressed mutation products lags far behind genomic (transcriptomic) analysis. With comprehensive global proteomics analysis, only a small percentage of single nucleotide variants detected by DNA and RNA sequencing have been observed as single amino acid variants due to current technical limitations. Proteomic analysis of mutations is important with the potential to advance cancer biomarker development and the discovery of new therapeutic targets for more effective disease treatment. Targeted proteomics using selected reaction monitoring (also known as multiple reaction monitoring) and parallel reaction monitoring, has emerged as a powerful tool with significant advantages over global proteomics for analysis of protein mutations in terms of detection sensitivity, quantitation accuracy and overall practicality (e.g., reliable identification and the scale of quantification). Herein we review recent advances in the targeted proteomics technology for enhancing detection sensitivity and multiplexing capability and highlight its broad biomedical applications for analysis of protein mutations in human bodily fluids, tissues, and cell lines. Furthermore, we review recent applications of top-down proteomics for analysis of protein mutations. Unlike the commonly used bottom-up proteomics which requires digestion of proteins into peptides, top-down proteomics directly analyzes intact proteins for more precise characterization of mutation isoforms. Finally, general perspectives on the potential of achieving both high sensitivity and high sample throughput for large-scale targeted detection and quantification of important protein mutations are discussed.

Rational policymaking during a pandemic.

Policymaking during a pandemic can be extremely challenging. As COVID-19 is a new disease and its global impacts are unprecedented, decisions are taken in a highly uncertain, complex, and rapidly changing environment. In such a context, in which human lives and the economy are at stake, we argue that using ideas and constructs from modern decision theory, even informally, will make policymaking a more responsible and transparent process.

MZA: A Data Conversion Tool to Facilitate Software Development and Artificial Intelligence Research in Multidimensional Mass Spectrometry.

Modern mass spectrometry-based workflows employing hybrid instrumentation and orthogonal separations collect multidimensional data, potentially allowing deeper understanding in omics studies through adoption of artificial intelligence methods. However, the large volume of these rich spectra challenges existing data storage and access technologies, therefore precluding informatics advancements. We present MZA (pronounced m-za), the mass-to-charge (m/z) generic data storage and access tool designed to facilitate software development and artificial intelligence research in multidimensional mass spectrometry measurements. Composed of a data conversion tool and a simple file structure based on the HDF5 format, MZA provides easy, cross-platform and cross-programming language access to raw MS-data, enabling fast development of new tools in data science programming languages such as Python and R. The software executable, example MS-data and example Python and R scripts are freely available at https://github.com/PNNL-m-q/mza.

Correction: Anticipatory changes in British household purchases of soft drinks associated with the announcement of the Soft Drinks Industry Levy: A controlled interrupted time series analysis.

[This corrects the article DOI: 10.1371/journal.pmed.1003269.].

Development of a Structure for Lossless Ion Manipulations (SLIM) High Charge Capacity Array of Traps.

Enhancing the sensitivity of low-abundance ions in a complex mixture without sacrificing measurement throughput is highly desirable. This work demonstrates a way to greatly improve the sensitivity of ion mobility (IM)-selected ions by accumulating them in an array of high-capacity ion traps located inside a novel structures for lossless ion manipulations ion mobility spectrometer (SLIM-IMS) module. The array of ion traps used in this work consisted of seven independently controllable traps. Each trap was 386 mm long and possessed a charge capacity of ∼4.5 × 108 charges, with a linear range extending to ∼2.5 × 108 charges. Each ion trap could be used to extract a peak (or ions over a mobility range) from an ion mobility separation based on arrival time. Ions could be stored without losses for long times (>100 s) and then released all at once or one trap at a time. It was possible to accumulate large ion populations by extracting and storing ions over repeated IM separations. Enrichment of up to seven individual ion distributions could be performed using the seven independently controllable ion traps. Additionally, the ion trapping process effectively compressed ion populations into narrow peaks, which provides a greatly improved basis for subsequent ion manipulations. The array of high charge capacity ion traps provides a flexible addition to SLIM and a powerful tool for IMS-MS applications requiring high sensitivity.

A Dual-Gated Structures for Lossless Ion Manipulations-Ion Mobility Orbitrap Mass Spectrometry Platform for Combined Ultra-High-Resolution Molecular Analysis.

High-resolution ion mobility spectrometry-mass spectrometry (HR-IMS-MS) instruments have enormously advanced the ability to characterize complex biological mixtures. Unfortunately, HR-IMS and HR-MS measurements are typically performed independently due to mismatches in analysis time scales. Here, we overcome this limitation by using a dual-gated ion injection approach to couple an 11 m path length structures for lossless ion manipulations (SLIM) module to a Q-Exactive Plus Orbitrap MS platform. The dual-gate setup was implemented by placing one ion gate before the SLIM module and a second ion gate after the module. The dual-gated ion injection approach allowed the new SLIM-Orbitrap platform to simultaneously perform an 11 m SLIM separation, Orbitrap mass analysis using the highest selectable mass resolution setting (up to 140 k), and high-energy collision-induced dissociation (HCD) in ∼25 min over an m/z range of ∼1500 amu. The SLIM-Orbitrap platform was initially characterized using a mixture of standard phosphazene cations and demonstrated an average SLIM CCS resolving power (RpCCS) of ∼218 and an SLIM peak capacity of ∼156, while simultaneously obtaining high mass resolutions. SLIM-Orbitrap analysis with fragmentation was then performed on mixtures of standard peptides and two reverse peptides (SDGRG1+, GRGDS1+, and RpCCS = 305) to demonstrate the utility of combined HR-IMS-MS/MS measurements for peptide identification. Our new HR-IMS-MS/MS capability was further demonstrated by analyzing a complex lipid mixture and showcasing SLIM separations on isobaric lipids. This new SLIM-Orbitrap platform demonstrates a critical new capability for proteomics and lipidomics applications, and the high-resolution multimodal data obtained using this system establish the foundation for reference-free identification of unknown ion structures.

Integrated Transcriptomic and Proteomic Analysis Identifies Plasma Biomarkers of Hepatocellular Failure in Alcohol-Associated Hepatitis.

Alcohol-associated hepatitis (AH) is a form of liver failure with high short-term mortality. Recent studies have shown that defective function of hepatocyte nuclear factor 4 alpha (HNF4a) and systemic inflammation are major disease drivers of AH. Plasma biomarkers of hepatocyte function could be useful for diagnostic and prognostic purposes. Herein, an integrative analysis of hepatic RNA sequencing and liquid chromatography-tandem mass spectrometry was performed to identify plasma protein signatures for patients with mild and severe AH. Alcohol-related liver disease cirrhosis, nonalcoholic fatty liver disease, and healthy subjects were used as comparator groups. Levels of identified proteins primarily involved in hepatocellular function were decreased in patients with AH, which included hepatokines, clotting factors, complement cascade components, and hepatocyte growth activators. A protein signature of AH disease severity was identified, including thrombin, hepatocyte growth factor α, clusterin, human serum factor H-related protein, and kallistatin, which exhibited large abundance shifts between severe and nonsevere AH. The combination of thrombin and hepatocyte growth factor α discriminated between severe and nonsevere AH with high sensitivity and specificity. These findings were correlated with the liver expression of genes encoding secreted proteins in a similar cohort, finding a highly consistent plasma protein signature reflecting HNF4A and HNF1A functions. This unbiased proteomic-transcriptome analysis identified plasma protein signatures and pathways associated with disease severity, reflecting HNF4A/1A activity useful for diagnostic assessment in AH.

The Role of Ion Rotation in Ion Mobility: Ultrahigh-Precision Prediction of Ion Mobility Dependence on Ion Mass Distribution and Translational to Rotational Energy Transfer.

The role of ion rotation in determining ion mobilities is explored using the subtle gas phase ion mobility shifts based on differences in ion mass distributions between isotopomer ions that have been observed with ion mobility spectrometry (IMS) measurements. These mobility shifts become apparent for IMS resolving powers on the order of ∼1500 where relative mobilities (or alternatively momentum transfer collision cross sections; Ω) can be measured with a precision of ∼10 ppm. The isotopomer ions have identical structures and masses, differing only in their internal mass distributions, and their Ω differences cannot be predicted by widely used computational approaches, which ignore the dependence of Ω on the ion's rotational properties. Here, we investigate the rotational dependence of Ω, which includes changes to its collision frequency due to thermal rotation as well as the coupling of translational to rotational energy transfer. We show that differences in rotational energy transfer during ion-molecule collisions provide the major contribution to isotopomer ion separations, with only a minor contribution due to an increase in collision frequency due to ion rotation. Modeling including these factors allowed for differences in Ω to be calculated that precisely mirror the experimental separations. These findings also highlight the promise of pairing high-resolution IMS measurements with theory and computation for improved elucidation of subtle structural differences between ions.

A multi-country comparison of jurisdictions with and without mandatory nutrition labelling policies in restaurants: analysis of behaviours associated with menu labelling in the 2019 International Food Policy Study.

OBJECTIVE: To examine differences in noticing and use of nutrition information comparing jurisdictions with and without mandatory menu labelling policies and examine differences among sociodemographic groups. DESIGN: Cross-sectional data from the International Food Policy Study (IFPS) online survey. SETTING: IFPS participants from Australia, Canada, Mexico, United Kingdom and USA in 2019. PARTICIPANTS: Adults aged 18-99; n 19 393. RESULTS: Participants in jurisdictions with mandatory policies were significantly more likely to notice and use nutrition information, order something different, eat less of their order and change restaurants compared to jurisdictions without policies. For noticed nutrition information, the differences between policy groups were greatest comparing older to younger age groups and comparing high education (difference of 10·7 %, 95 % CI 8·9, 12·6) to low education (difference of 4·1 %, 95 % CI 1·8, 6·3). For used nutrition information, differences were greatest comparing high education (difference of 4·9 %, 95 % CI 3·5, 6·4) to low education (difference of 1·8 %, 95 % CI 0·2, 3·5). Mandatory labelling was associated with an increase in ordering something different among the majority ethnicity group and a decrease among the minority ethnicity group. For changed restaurant visited, differences were greater for medium and high education compared to low education, and differences were greater for higher compared to lower income adequacy. CONCLUSIONS: Participants living in jurisdictions with mandatory nutrition information in restaurants were more likely to report noticing and using nutrition information, as well as greater efforts to modify their consumption. However, the magnitudes of these differences were relatively small.

Evaluating Software Tools for Lipid Identification from Ion Mobility Spectrometry-Mass Spectrometry Lipidomics Data.

The unambiguous identification of lipids is a critical component of lipidomics studies and greatly impacts the interpretation and significance of analyses as well as the ultimate biological understandings derived from measurements. The level of structural detail that is available for lipid identifications is largely determined by the analytical platform being used. Mass spectrometry (MS) coupled with liquid chromatography (LC) is the predominant combination of analytical techniques used for lipidomics studies, and these methods can provide fairly detailed lipid identification. More recently, ion mobility spectrometry (IMS) has begun to see greater adoption in lipidomics studies thanks to the additional dimension of separation that it provides and the added structural information that can support lipid identification. At present, relatively few software tools are available for IMS-MS lipidomics data analysis, which reflects the still limited adoption of IMS as well as the limited software support. This fact is even more pronounced for isomer identifications, such as the determination of double bond positions or integration with MS-based imaging. In this review, we survey the landscape of software tools that are available for the analysis of IMS-MS-based lipidomics data and we evaluate lipid identifications produced by these tools using open-access data sourced from the peer-reviewed lipidomics literature.

A Preprocessing Tool for Enhanced Ion Mobility-Mass Spectrometry-Based Omics Workflows.

The ability to improve the data quality of ion mobility-mass spectrometry (IM-MS) measurements is of great importance for enabling modular and efficient computational workflows and gaining better qualitative and quantitative insights from complex biological and environmental samples. We developed the PNNL PreProcessor, a standalone and user-friendly software housing various algorithmic implementations to generate new MS-files with enhanced signal quality and in the same instrument format. Different experimental approaches are supported for IM-MS based on Drift-Tube (DT) and Structures for Lossless Ion Manipulations (SLIM), including liquid chromatography (LC) and infusion analyses. The algorithms extend the dynamic range of the detection system, while reducing file sizes for faster and memory-efficient downstream processing. Specifically, multidimensional smoothing improves peak shapes of poorly defined low-abundance signals, and saturation repair reconstructs the intensity profile of high-abundance peaks from various analyte types. Other functionalities are data compression and interpolation, IM demultiplexing, noise filtering by low intensity threshold and spike removal, and exporting of acquisition metadata. Several advantages of the tool are illustrated, including an increase of 19.4% in lipid annotations and a two-times faster processing of LC-DT IM-MS data-independent acquisition spectra from a complex lipid extract of a standard human plasma sample. The software is freely available at https://omics.pnl.gov/software/pnnl-preprocessor.