Optimization of data-dependent acquisition parameters for coupling high-speed separations with LC-MS/MS for protein identifications

Immunogenic peptides putatively from intratumor microbes: Opportunities for colorectal cancer treatment

Recent evidence has confirmed the presence of intratumor microbes, yet their impact on the immunopeptidome remains largely unexplored. Here we introduced an integrated strategy to identify the immunopeptidome originated from intratumor microbes. Analyzing 10 colorectal cancer (CRC) patients, we identified 154 putative microbe-derived human leukocyte antigen (HLA)-I ligands. Predominantly bacterial in origin, these peptides were notably abundant in Fusobacterium nucleatum, the most prevalent bacterium differentiating between normal and tumor tissues. We discovered 20 peptides originating from F. nucleatum, thirteen of which, including two peptides shared across multiple patients, were tumor specific. Validation experiments confirmed that the putative microbe-derived peptide could activate CD8+ T cell responses. Our findings indicate that HLA-I molecules are capable of presenting intratumor microbe-derived peptides in CRC, potentially contributing to CD8+ T cell-mediated immunity and suggesting potential strategies for cancer immunotherapy.

Proteomics for Microalgae Extracts by High-Resolution Mass Spectrometry

Two protocols of protein extraction from Arthrospira platensis (spirulina) microalgae to study their proteome by mass spectrometry (MS) are here presented. The first is based on an aqueous buffer solution of Tris-HCl and the second on cold acetone. The identification of proteins was carried out by a bottom-up approach, which involves enzymatic digestion of extracted proteins followed by either matrix-assisted laser desorption ionization with time-of-flight (MALDI-TOF) MS or liquid chromatography (LC) coupled with electrospray ionization (ESI) and Fourier-transform tandem MS. While MALDI-TOF MS allowed for a fast peptide mass fingerprinting (PMF) check yet identifying less than 20 proteins in the extracted samples, the data-dependent acquisitions (DDA) mode of reversed-phase (RP) LC-ESI tandem FTMS/MS separations allowed us to recognize more than one hundred proteins by searching into dedicated spectral libraries. The application of MALDI-TOF MS analysis was found, however, of great support for preliminary investigations of cyanobacteria samples before proceeding with the RPLC-ESI-MS/MS DDA investigation, which definitively allows for a qualitative proteome analysis also of minor spirulina proteins in processed foodstuffs. Although the protein content in spirulina can be influenced by cultivation and environmental conditions, e.g., light intensity, climate, and water/air quality, here the qualitative chemical profiles of the examined samples were characterized by similar composition in high-quality proteins as phycocyanins and phycoerythrins.

Visualisation of proteome-wide ordered protein abundances in Trypanosoma brucei

Background: Trypanosoma brucei is a protozoan parasite and etiological agent of human and animal African trypanosomiasis. It has a complex life cycle, but the most studied cellular types are the in vitro cultivated bloodstream- and procyclic-forms. These correspond to the replicating, mammalian host bloodstream-dwelling, slender trypomastigotes and tsetse vector midgut-dwelling procyclic lifecycle stages, respectively. Several proteomics studies have reported the differential abundance of proteins between these in vitro cultivated cell types. However, there are no datasets providing protein abundance, from most to least abundant, within and between both cell types. Methods: We used MaxQuant software 1.6.10.4 to reprocess a recent large-scale proteomics experiment from our laboratory and extracted intensity-based quantifications of the bloodstream and procyclic form proteomes. Results: We created a web interface to visually explore protein abundances within and between the in vitro cultivated T. brucei bloodstream and procyclic form proteomes. Conclusions: The protein abundance visualization tool, searchable by protein name(s) and attribute(s), is likely to be useful to the trypanosome research community. It will allow users to contextualise their proteins of interest in terms of their abundances in the T. brucei bloodstream and procyclic form proteomes.

Visualisation of proteome-wide ordered protein abundances in Trypanosoma brucei

Background: Trypanosoma brucei is a protozoan parasite and etiological agent of human and animal African trypanosomiasis. It has a complex life cycle, but the most studied cellular types are the in vitro cultivated bloodstream- and procyclic-forms. These correspond to the replicating, mammalian host bloodstream-dwelling, slender trypomastigotes and tsetse vector midgut-dwelling procyclic lifecycle stages, respectively. Several proteomics studies have reported the differential abundance of proteins between these in vitro cultivated cell types. However, there are no datasets providing protein abundance, from most to least abundant, within and between both cell types. Methods: We used MaxQuant software 1.6.10.4 to reprocess a recent large-scale proteomics experiment from our laboratory and extracted intensity-based quantifications of the bloodstream and procyclic form proteomes. Results: We created a web interface to visually explore protein abundances within and between the in vitro cultivated T. brucei bloodstream and procyclic form proteomes. Conclusions: The protein abundance visualization tool, searchable by protein name(s) and attribute(s), is likely to be useful to the trypanosome research community. It will allow users to contextualise their proteins of interest in terms of their abundances in the T. brucei bloodstream and procyclic form proteomes.

Eight key rules for successful data-dependent acquisition in mass spectrometry-based metabolomics

In recent years, metabolomics has emerged as a pivotal approach for the holistic analysis of metabolites in biological systems. The rapid progress in analytical equipment, coupled to the rise of powerful data processing tools, now provides unprecedented opportunities to deepen our understanding of the relationships between biochemical processes and physiological or phenotypic conditions in living organisms. However, to obtain unbiased data coverage of hundreds or thousands of metabolites remains a challenging task. Among the panel of available analytical methods, targeted and untargeted mass spectrometry approaches are among the most commonly used. While targeted metabolomics usually relies on multiple-reaction monitoring acquisition, untargeted metabolomics use either data-independent acquisition (DIA) or data-dependent acquisition (DDA) methods. Unlike DIA, DDA offers the possibility to get real, selective MS/MS spectra and thus to improve metabolite assignment when performing untargeted metabolomics. Yet, DDA settings are more complex to establish than DIA settings, and as a result, DDA is more prone to errors in method development and application. Here, we present a tutorial which provides guidelines on how to optimize the technical parameters essential for proper DDA experiments in metabolomics applications. This tutorial is organized as a series of rules describing the impact of the different parameters on data acquisition and data quality. It is primarily intended to metabolomics users and mass spectrometrists that wish to acquire both theoretical background and practical tips for developing effective DDA methods.

Interfaces with Structure Dynamics of the Workhorses from Cells Revealed through Cross-Linking Mass Spectrometry (CLMS)

The fundamentals of how protein-protein/RNA/DNA interactions influence the structures and functions of the workhorses from the cells have been well documented in the 20th century. A diverse set of methods exist to determine such interactions between different components, particularly, the mass spectrometry (MS) methods, with its advanced instrumentation, has become a significant approach to analyze a diverse range of biomolecules, as well as bring insights to their biomolecular processes. This review highlights the principal role of chemistry in MS-based structural proteomics approaches, with a particular focus on the chemical cross-linking of protein-protein/DNA/RNA complexes. In addition, we discuss different methods to prepare the cross-linked samples for MS analysis and tools to identify cross-linked peptides. Cross-linking mass spectrometry (CLMS) holds promise to identify interaction sites in larger and more complex biological systems. The typical CLMS workflow allows for the measurement of the proximity in three-dimensional space of amino acids, identifying proteins in direct contact with DNA or RNA, and it provides information on the folds of proteins as well as their topology in the complexes. Principal CLMS applications, its notable successes, as well as common pipelines that bridge proteomics, molecular biology, structural systems biology, and interactomics are outlined.

Data-Independent Acquisition for the Quantification and Identification of Metabolites in Plasma

A popular fragmentation technique for non-targeted analysis is called data-independent acquisition (DIA), because it provides fragmentation data for all analytes in a specific mass range. In this work, we demonstrated the strengths and weaknesses of DIA. Two types of chromatography (fractionation/3 min and hydrophilic interaction liquid chromatography (HILIC)/18 min) and three DIA protocols (variable sequential window acquisition of all theoretical mass spectra (SWATH), fixed SWATH and MS^ALL) were used to evaluate the performance of DIA. Our results show that fast chromatography and MS^ALL often results in product ion overlap and complex MS/MS spectra, which reduces the quantitative and qualitative power of these DIA protocols. The combination of SWATH and HILIC allowed for the correct identification of 20 metabolites using the NIST library. After SWATH window customization (i.e., variable SWATH), we were able to quantify ten structural isomers with a mean accuracy of 103% (91-113%). The robustness of the variable SWATH and HILIC method was demonstrated by the accurate quantification of these structural isomers in 10 highly diverse blood samples. Since the combination of variable SWATH and HILIC results in good quantitative and qualitative fragmentation data, it is promising for both targeted and untargeted platforms. This should decrease the number of platforms needed in metabolomics and increase the value of a single analysis.

ESTIMATION AND INFERENCE IN METABOLOMICS WITH NON-RANDOM MISSING DATA AND LATENT FACTORS

High throughput metabolomics data are fraught with both non-ignorable missing observations and unobserved factors that influence a metabolite's measured concentration, and it is well known that ignoring either of these complications can compromise estimators. However, current methods to analyze these data can only account for the missing data or unobserved factors, but not both. We therefore developed MetabMiss, a statistically rigorous method to account for both non-random missing data and latent factors in high throughput metabolomics data. Our methodology does not require the practitioner specify a likelihood for the missing data, and makes investigating the relationship between the metabolome and tens, or even hundreds, of phenotypes computationally tractable. We demonstrate the fidelity of Metab-Miss's estimates using both simulated and real metabolomics data, and prove their asymptotic correctness when the sample size and number of metabolites grows to infinity.

Aconitase Functions as a Pleiotropic Posttranscriptional Regulator in Helicobacter pylori

Posttranscriptional regulation in bacteria has increasingly become recognized as playing a major role in response to environmental stimuli. Aconitase is a bifunctional protein that not only acts enzymatically but also can be a posttranscriptional regulator. To investigate protein expression regulated by Helicobacter pylori AcnB in response to oxidative stress, a global proteomics study was conducted wherein the ΔacnB strain was compared to the parent strain when both strains were O2 stressed. Many proteins, including some involved in urease activity, in combating oxidative stress, and in motility, were expressed at a significantly lower level in the ΔacnB strain. A bioinformatics prediction tool was used to identify putative targets for aconitase-mediated regulation, and electrophoretic mobility shift assays demonstrated that apo-AcnB is able to bind to RNA transcripts of hpn (encoding a nickel-sequestering protein), ahpC (encoding alkyl hydroperoxide reductase), and flgR (encoding flagellum response regulator). Compared to the wild type (WT), the ΔacnB strain had decreased activities of the nickel-containing enzymes urease and hydrogenase, and this could be correlated with lower total nickel levels within ΔacnB cells. Binding of apo-AcnB to the hpn 5' untranslated region (UTR) may inhibit the expression of Hpn. In agreement with the finding that AcnB regulates the expression of antioxidant proteins such as AhpC, ΔacnB cells displayed oxidative-stress-sensitive phenotypes. The ΔacnB strain has a lesser motility ability than the WT strain, which can likely be explained by the functions of AcnB on the FlgRS-RpoN-FlgE regulatory cascade. Collectively, our results suggest a global role for aconitase as a posttranscriptional regulator in this gastric pathogen.

IMPORTANCE

Bacterial survival depends on the ability of the cell to sense and respond to a variety of environmental changes. For Helicobacter pylori, responding to environmental stimuli within the gastric niche is essential for persistence and host colonization. However, there is much to be learned about the regulatory mechanisms that H. pylori employs to orchestrate its response to different stimuli. In this study, we explore the role of aconitase, a bifunctional protein that has been found to act as a posttranscriptional regulator in several other bacteria. Our results shed light on the magnitude of aconitase-mediated regulation in H. pylori, and we propose that aconitase acts as a global regulator of key genes involved in virulence.

On an aerodynamic mechanism to enhance ion transmission and sensitivity of FAIMS for nano-electrospray ionization-mass spectrometry

Simulations show that significant ion losses occur within the commercial electrospray ionization-field asymmetric waveform ion mobility spectrometer (ESI-FAIMS) interface owing to an angular desolvation gas flow and because of the impact of the FAIMS carrier gas onto the inner rf (radio frequency) electrode. The angular desolvation gas flow diverts ions away from the entrance plate orifice while the carrier gas annihilates ions onto the inner rf electrode. A novel ESI-FAIMS interface is described that optimizes FAIMS gas flows resulting in large improvements in transmission. Simulations with the bromochloroacetate anion showed an improvement of ~9-fold to give ~70% overall transmission). Comparable transmission improvements were attained experimentally for six peptides (2+) in the range of m/z 404.2 to 653.4 at a chromatographic flow rate of 300 nL/min. Selected ion chromatograms (SIC) from nano-LC-FAIMS-MS analyses showed 71% (HLVDEPQNLIK, m/z 653.4, 2+) to 95% (LVNELTEFAK, m/z 582.3, 2+) of ion signal compared with ion signal in the SIC from LC-MS analysis. IGSEVYHNLK (580.3, 2+) showed 24% more ion signal compared with LC-MS and is explained by enhanced desolvation in FAIMS. A 3-10 times lower limits of quantitation (LOQ) (<15% RSD) was achieved for chemical noise limited peaks with FAIMS. Peaks limited by ion statistics showed subtle improvement in RSD and yielded comparable LOQ to that attained with nano-LC-MS (without FAIMS). These improvements were obtained using a reduced FAIMS separation gap (from 2.5 to 1.5 mm) that results in a shorter residence time (13.2 ms ± 3.9 ms) and enables the use of a helium free transport gas (100% nitrogen).

The use of ammonium formate as a mobile-phase modifier for LC-MS/MS analysis of tryptic digests

A major challenge facing current mass spectrometry (MS)-based proteomics research is the large concentration range displayed in biological systems, which far exceeds the dynamic range of commonly available mass spectrometers. One approach to overcome this limitation is to improve online reversed-phase liquid chromatography (RP-LC) separation methodologies. LC mobile-phase modifiers are used to improve peak shape and increase sample load tolerance. Trifluoroacetic acid (TFA) is a commonly used mobile-phase modifier, as it produces peptide separations that are far superior to other additives. However, TFA leads to signal suppression when incorporated with electrospray ionization (ESI), and thus, other modifiers, such as formic acid (FA), are used for LC-MS applications. FA exhibits significantly less signal suppression, but is not as effective of a modifier as TFA. An alternative mobile-phase modifier is the combination of FA and ammonium formate (AF), which has been shown to improve peptide separations. The ESI-MS compatibility of this modifier has not been investigated, particularly for proteomic applications. This work compares the separation metrics of mobile phases modified with FA and FA/AF and explores the use of FA/AF for the LC-MS analysis of tryptic digests. Standard tryptic-digest peptides were used for comparative analysis of peak capacity and sample load tolerance. The compatibility of FA/AF in proteomic applications was examined with the analysis of soluble proteins from canine prostate carcinoma tissue. Overall, the use of FA/AF improved online RP-LC separations and led to significant increases in peptide identifications with improved protein sequence coverage.