Insights into modifiers effects in differential mobility spectrometry: A data science approach for metabolomics and peptidomics.

Utilizing a data-driven approach, this study investigates modifier effects on compensation voltage in differential mobility spectrometry-mass spectrometry (DMS-MS) for metabolites and peptides. Our analysis uncovers specific factors causing signal suppression in small molecules and pinpoints both signal suppression mechanisms and the analytes involved. In peptides, machine learning models discern a relationship between molecular weight, topological polar surface area, peptide charge, and proton transfer-induced signal suppression. The models exhibit robust performance, offering valuable insights for the application of DMS to metabolites and tryptic peptides analysis by DMS-MS.

A Workflow for Improved Analysis of Cross-Linking Mass Spectrometry Data Integrating Parallel Accumulation-Serial Fragmentation with MeroX and Skyline.

Cross-linking mass spectrometry (XL-MS) has evolved into a pivotal technique for probing protein interactions. This study describes the implementation of Parallel Accumulation-Serial Fragmentation (PASEF) on timsTOF instruments, enhancing the detection and analysis of protein interactions by XL-MS. Addressing the challenges in XL-MS, such as the interpretation of complex spectra, low abundant cross-linked peptides, and a data acquisition bias, our current study integrates a peptide-centric approach for the analysis of XL-MS data and presents the foundation for integrating data-independent acquisition (DIA) in XL-MS with a vendor-neutral and open-source platform. A novel workflow is described for processing data-dependent acquisition (DDA) of PASEF-derived information. For this, software by Bruker Daltonics is used, enabling the conversion of these data into a format that is compatible with MeroX and Skyline software tools. Our approach significantly improves the identification of cross-linked products from complex mixtures, allowing the XL-MS community to overcome current analytical limitations.

Label-free detection and profiling of individual solution-phase molecules.

Most chemistry and biology occurs in solution, in which conformational dynamics and complexation underlie behaviour and function. Single-molecule techniques1 are uniquely suited to resolving molecular diversity and new label-free approaches are reshaping the power of single-molecule measurements. A label-free single-molecule method2-16 capable of revealing details of molecular conformation in solution17,18 would allow a new microscopic perspective of unprecedented detail. Here we use the enhanced light-molecule interactions in high-finesse fibre-based Fabry-Pérot microcavities19-21 to detect individual biomolecules as small as 1.2 kDa, a ten-amino-acid peptide, with signal-to-noise ratios (SNRs) >100, even as the molecules are unlabelled and freely diffusing in solution. Our method delivers 2D intensity and temporal profiles, enabling the distinction of subpopulations in mixed samples. Notably, we observe a linear relationship between passage time and molecular radius, unlocking the potential to gather crucial information about diffusion and solution-phase conformation. Furthermore, mixtures of biomolecule isomers of the same molecular weight and composition but different conformation can also be resolved. Detection is based on the creation of a new molecular velocity filter window and a dynamic thermal priming mechanism that make use of the interplay between optical and thermal dynamics22,23 and Pound-Drever-Hall (PDH) cavity locking24 to reveal molecular motion even while suppressing environmental noise. New in vitro ways of revealing molecular conformation, diversity and dynamics can find broad potential for applications in the life and chemical sciences.

A Mass Spectrometry Strategy for Protein Quantification Based on the Differential Alkylation of Cysteines Using Iodoacetamide and Acrylamide.

Mass spectrometry has become the most prominent yet evolving technology in quantitative proteomics. Today, a number of label-free and label-based approaches are available for the relative and absolute quantification of proteins and peptides. However, the label-based methods rely solely on the employment of stable isotopes, which are expensive and often limited in availability. Here we propose a label-based quantification strategy, where the mass difference is identified by the differential alkylation of cysteines using iodoacetamide and acrylamide. The alkylation reactions were performed under identical experimental conditions; therefore, the method can be easily integrated into standard proteomic workflows. Using high-resolution mass spectrometry, the feasibility of this approach was assessed with a set of tryptic peptides of human serum albumin. Several critical questions, such as the efficiency of labeling and the effect of the differential alkylation on the peptide retention and fragmentation, were addressed. The concentration of the quality control samples calculated against the calibration curves were within the ±20% acceptance range. It was also demonstrated that heavy labeled peptides exhibit a similar extraction recovery and matrix effect to light ones. Consequently, the approach presented here may be a viable and cost-effective alternative of stable isotope labeling strategies for the quantification of cysteine-containing proteins.

Study on phosphonylation and modification characteristics of organophosphorus nerve agents on multi-species and multi-source albumins.

Protein adducts are vital targets for exploring organophosphorus nerve agents (OPNAs) exposure and identification, that can be used to characterize the chemical burden and initiate chemical safety measures. However, the use of protein adducts as biomarkers of OPNA exposure has developed slowly. To further promote the development of biomarkers in chemical forensics, it is crucial to expand the range of modified peptides and active sites, and describe the characteristics of OPNA adducts at specific reaction sites. This study utilized multi-species and multi-source albumins as the protein targets. We identified 56 peptides in albumins from various species (including human, horse, rat and pig), that were modified by at least two OPNAs. Diverse modification characteristics were observed in response to certain agents: including (1) multiple sites on the same peptide modified by one or more agents, (2) different reactivities at the same site in homologous albumins, and (3) different preferences at the same active sites associated with differences in the biological matrix during exposure. Our studies provided an empirical reference with rationalized underpinnings supported by estimated conformation energetics through molecular modeling. We employed different peptide markers for detection of protein adducts, as (one would do) in forensic screening for identification and quantification of chemical damage. Three characteristic peptides were screened and analyzed in human albumin, including Y287ICENQDSISSK, K438VPQVS443TPTLVEVSR, and Y162LY164EIAR. Stable fragment ions with neutral loss were found from their tandem MS/MS spectra, which were used as characteristic ions for identification and extraction of modified peptides in enzymatic digestion mixtures. Coupling these observations with computer simulations, we found that the structural stability of albumin and albumin-adduct complexes (as well as the effective force that promotes stability of different adducts) changes in the interval before and after adduct formation. In pig albumin, five active peptides existed stably in vivo and in vitro. Most of them can be detected within 30 min after OPNA exposure, and the detection window can persist about half a month. These early findings provided the foundation and rationale for utilizing pig albumin as a sampling target for rapid analysis in future forensic work.

Discrimination of Aspartic and Isoaspartic Acid Residues in Peptides by Tandem Mass Spectrometry with Hydrogen Attachment Dissociation.

Long-lived proteins undergo chemical modifications that can cause age-related diseases. Among these chemical modifications, isomerization is the most difficult to identify. Isomerization often occurs at the aspartic acid (Asp) residues. In this study, we used tandem mass spectrometry equipped with a newly developed ion activation method, hydrogen attachment dissociation (HAD), to analyze peptides containing Asp isomers. Although HAD preferentially produces [cn + 2H]+ and [zm + 2H]+ via N-Cα bond cleavage, [cn + 58 + 2H]+ and [zm - 58 + 2H]+ originate from the fragmentation of the isoAsp residue. Notably, [cn + 58 + 2H]+ and [zm - 58 + 2H]+ could be used as diagnostic fragment ions for the isoAsp residue because these fragment ions did not originate from the Asp residue. The detailed fragmentation mechanism was investigated by computational analysis using density functional theory. According to the results, hydrogen attachment to the carbonyl oxygen in the isoAsp residue results in the Cα-Cß bond cleavage. The experimental and theoretical joint study indicates that the present method allows us to discriminate Asp and isoAsp residues, including site identification of the isoAsp residue. Moreover, we demonstrated that the molar ratio of peptide isomers in the mixture could be estimated from their fragment ion abundance. Therefore, tandem mass spectrometry with HAD is a useful method for the rapid discrimination and semiquantitative analysis of peptides containing isoAsp residues.

Negative-Ion Electron Capture Dissociation of MALDI-Generated Peptide Anions.

Negative-ion electron capture dissociation (niECD) is an anion MS/MS technique that provides fragmentation analogous to conventional ECD, including high peptide sequence coverage and retention of labile post-translational modifications (PTMs). niECD has been proposed to be the most efficient for salt-bridged zwitterionic precursor ion structures. Several important PTMs, e.g., sulfation and phosphorylation, are acidic and can, therefore, be challenging to characterize in the positive-ion mode. Furthermore, PTM-friendly techniques, such as ECD, require multiple precursor ion-positive charges. By contrast, singly charged ions, refractory to ECD, are most compatible with niECD. Because electrospray ionization (ESI) typically yields multiply charged ions, we sought to explore matrix-assisted laser desorption/ionization (MALDI) in combination with niECD. However, the requirement for zwitterionic gaseous structures may preclude efficient niECD of MALDI-generated anions. Unexpectedly, we found that niECD of anions from MALDI is not only possible but proceeds with similar or higher efficiency compared with ESI-generated anions. Matrix selection did not appear to have a major effect. With MALDI, niECD is demonstrated up to m/z ∼4300. For such larger analytes, multiple electron captures are observed, resulting in triply charged fragments from singly charged precursor ions. Such charge-increased fragments show improved detectability. Furthermore, significantly improved (∼20-fold signal-to-noise increase) niECD spectral quality is achieved with equivalent sample amounts from MALDI vs ESI. Overall, the reported combination with MALDI significantly boosts the analytical utility of niECD.

Exact Integral Formulas for False Discovery Rate and the Variance of False Discovery Proportion.

Multiple hypothesis testing is an integral component of data analysis for large-scale technologies such as proteomics, transcriptomics, or metabolomics, for which the false discovery rate (FDR) and positive FDR (pFDR) have been accepted as error estimation and control measures. The pFDR is the expectation of false discovery proportion (FDP), which refers to the ratio of the number of null hypotheses to that of all rejected hypotheses. In practice, the expectation of ratio is approximated by the ratio of expectation; however, the conditions for transforming the former into the latter have not been investigated. This work derives exact integral expressions for the expectation (pFDR) and variance of FDP. The widely used approximation (ratio of expectations) is shown to be a particular case (in the limit of a large sample size) of the integral formula for pFDR. A recurrence formula is provided to compute the pFDR for a predefined number of null hypotheses. The variance of FDP was approximated for a practical application in peptide identification using forward and reversed protein sequences. The simulations demonstrate that the integral expression exhibits better accuracy than the approximate formula in the case of a small number of hypotheses. For large sample sizes, the pFDRs obtained by the integral expression and approximation do not differ substantially. Applications to proteomics data sets are included.

Discrimination of three commercial tuna species through species-specific peptides: From high-resolution mass spectrometry discovery to MRM validation.

The risk of tuna adulteration is high driven by economic benefits. The authenticity of tuna is required to protect both consumers and tuna stocks. Given this, the study is designed to identify species-specific peptides for distinguishing three commercial tropical tuna species. The peptides derived from trypsin digestion were separated and detected using ultrahigh-performance liquid chromatography-quadrupole-time of flight mass spectrometry (UPLC-Q-TOF/MS) in data-dependent acquisition (DDA) mode. Venn analysis showed that there were differences in peptide composition among the three tested tuna species. The biological specificity screening through the National Center for Biotechnology Information's Basic Local Alignment Search Tool (NCBI BLAST) revealed that 93 peptides could serve as potential species-specific peptides. Finally, the detection specificity of species-specific peptides of raw meats and processed products was carried out by multiple reaction monitoring (MRM) mode based on a Q-Trap mass spectrometer. The results showed that three, one and two peptides of Katsuwonus pelamis, Thunnus obesus and Thunnus albacores, respectively could serve as species-specific peptides.

Improved Data Acquisition Settings on Q Exactive HF-X and Fusion Lumos Tribrid Orbitrap-Based Mass Spectrometers for Proteomic Analysis of Limited Samples.

Deep proteomic profiling of complex biological and medical samples available at low nanogram and subnanogram levels is still challenging. Thorough optimization of settings, parameters, and conditions in nanoflow liquid chromatography-tandem mass spectrometry (MS)-based proteomic profiling is crucial for generating informative data using amount-limited samples. This study demonstrates that by adjusting selected instrument parameters, e.g., ion injection time, automated gain control, and minimally altering the conditions for resuspending or storing the sample in solvents of different compositions, up to 15-fold more thorough proteomic profiling can be achieved compared to conventionally used settings. More specifically, the analysis of 1 ng of the HeLa protein digest standard by Q Exactive HF-X Hybrid Quadrupole-Orbitrap and Orbitrap Fusion Lumos Tribrid mass spectrometers yielded an increase from 1758 to 5477 (3-fold) and 281 to 4276 (15-fold) peptides, respectively, demonstrating that higher protein identification results can be obtained using the optimized methods. While the instruments applied in this study do not belong to the latest generation of mass spectrometers, they are broadly used worldwide, which makes the guidelines for improving performance desirable to a wide range of proteomics practitioners.

Optimizing Spectronaut Search Parameters to Improve Data Quality with Minimal Proteome Coverage Reductions in DIA Analyses of Heterogeneous Samples.

Data-independent acquisition has seen breakthroughs that enable comprehensive proteome profiling using short gradients. As the proteome coverage continues to increase, the quality of the data generated becomes much more relevant. Using Spectronaut, we show that the default search parameters can be easily optimized to minimize the occurrence of false positives across different samples. Using an immunological infection model system to demonstrate the impact of adjusting search settings, we analyzed Mus musculus macrophages and compared their proteome to macrophages spiked withCandida albicans. This experimental system enabled the identification of "false positives" as Candida albicans peptides and proteins should not be present in the Mus musculus-only samples. We show that adjusting the search parameters reduced "false positive" identifications by 89% at the peptide and protein level, thereby considerably increasing the quality of the data. We also show that these optimized parameters incurred a moderate cost, only reducing the overall number of "true positive" identifications across each biological replicate by <6.7% at both the peptide and protein level. We believe the value of our updated search parameters extends beyond a two-organism analysis and would be of great value to any DIA experiment analyzing heterogeneous populations of cell types or tissues.

Investigation of liquid chromatography-mass spectrometry analysis of a peptide aldehyde SJA6017 with identifying its hemiacetal, gem-diol, and enol ether.

The quantitative analysis of SJA6017, a peptide aldehyde inhibitor of calpain (Calpain Inhibitor VI), has encountered challenges in preclinical drug studies. The complex reverse-phase HPLC chromatographic behavior exhibits two peaks, each containing multiple species. An liquid chromatography-mass spectrometry (LC-MS/MS) study proposed an explanation for this phenomenon, caused by the amide aldehyde structure of SJA6017. Four chemical species corresponding to the two HPLC peaks have been identified as SJA6017 and its methyl hemiacetal, methyl enol ether, and gem-diol. In many instances of preclinical studies, methanol is favored as a substitute for DMSO. The hemiacetal is formed when the amide-activated peptide aldehyde reacts with methanol, which can then be further dehydrated in the mass spectrometer ion source under high temperature to form the methyl enol ether. The hemiacetal and gem-diol can also be decomposed to SJA6017 in the ion source. Additionally, the amide-activated peptide aldehyde can easily hydrate to the gem-diol of SJA6017 during sample incubation or sample preparation. The hemiacetal and gem-diol of SJA6017 are stable enough to have different retention times in the liquid chromatography, which explains why SJA6017 appears as two peaks, each containing multiple species. An LC-MS/MS tandem quadrupole mass spectrometer quantitative analysis method is proposed, enabling the analysis of these types of samples. This work serves as both an illustrative example and a cautionary note for mass analysis, sample incubations, and sample preparations involving compounds of peptide aldehyde, including similar aldehyde-containing metabolites, especially when methanol is present. This study provides the information needed to understand peptide aldehyde behavior at various steps of preclinical in vitro studies in the presence of methanol. It has assisted in the development of the SJA6017 bioanalysis method and will also aid in the development of bioanalysis methods for similar peptide aldehydes.

Improved assay development of pharmaceutical modalities using feedback-controlled liquid chromatography optimization.

Development of meaningful and reliable analytical assays in the (bio)pharmaceutical industry can often be challenging, involving tedious trial and error experimentation. In this work, an automated analytical workflow using an AI-based algorithm for streamlined method development and optimization is presented. Chromatographic methods are developed and optimized from start to finish by a feedback-controlled modeling approach using readily available LC instrumentation and software technologies, bypassing manual user intervention. With the use of such tools, the time requirement of the analyst is drastically minimized in the development of a method. Herein key insights on chromatography system control, automatic optimization of mobile phase conditions, and final separation landscape for challenging multicomponent mixtures are presented (e.g., small molecules drug, peptides, proteins, and vaccine products) showcased by a detailed comparison of a chiral method development process. The work presented here illustrates the power of modern chromatography instrumentation and AI-based software to accelerate the development and deployment of new separation assays across (bio)pharmaceutical modalities while yielding substantial cost-savings, method robustness, and fast analytical turnaround.

Synthetic Knockout Protein Standard for Evaluating Interference in Tandem Mass Tag-Based Proteomics.

Isobaric labeling is widely used for unbiased, proteome-wide studies, and it provides several advantages, such as fewer missing values among samples and higher quantitative precision. However, ion interference may lead to compressed or distorted observed ratios due to the coelution and coanalysis of peptides. Here, we introduced a synthetic KnockOut standard (sKO) for evaluating interference in tandem mass tags-based proteomics. sKO is made by mixing TMTpro-labeled tryptic peptides derived from four nonhuman proteins and a whole human proteome as background at different proportions. We showcased the utility of the sKO standard by exploring ion interference at different peptide concentrations (up to a 30-fold change in abundance) and using a variety of mass spectrometer data acquisition strategies. We also demonstrated that the sKO standard could provide valuable information for the rational design of acquisition strategies to achieve optimal data quality and discussed its potential applications for high-throughput proteomics workflows development.

Inserting Pre-analytical Chromatographic Priming Runs Significantly Improves Targeted Pathway Proteomics with Sample Multiplexing.

GoDig, a platform for targeted pathway proteomics without the need for manual assay scheduling or synthetic standards, is a powerful, flexible, and easy-to-use method that uses tandem mass tags to increase sample throughput up to 18-fold relative to label-free methods. Though the protein-level success rates of GoDig are high, the peptide-level success rates are more limited, hampering assays of harder-to-quantify proteins and site-specific phenomena. To guide the optimization of GoDig assays as well as improvements to the GoDig platform, we created GoDigViewer, a new stand-alone software that provides detailed visualizations of GoDig runs. GoDigViewer guided the implementation of "priming runs," an acquisition mode with significantly higher success rates. In this mode, two or more chromatographic priming runs are automatically performed to improve the accuracy and precision of target elution orders, followed by analytical runs which quantify targets. Using priming runs, success rates exceeded 97% for a list of 400 peptide targets and 95% for a list of 200 targets that are usually not quantified using untargeted mass spectrometry. We used priming runs to establish a quantitative assay of 125 macroautophagy proteins that had a >95% success rate and revealed differences in macroautophagy expression profiles across four human cell lines.

Improved Detection of Tryptic Peptides from Tissue Sections Using Desorption Electrospray Ionization Mass Spectrometry Imaging.

DESI-MSI is an ambient ionization technique used frequently for the detection of lipids, small molecules, and drug targets. Until recently, DESI had only limited use for the detection of proteins and peptides due to the setup and needs around deconvolution of data resulting in a small number of species being detected at lower spatial resolution. There are known differences in the ion species detected using DESI and MALDI for nonpeptide molecules, and here, we identify that this extends to proteomic species. DESI MS images were obtained for tissue sections of mouse and rat brain using a precommercial heated inlet (approximately 450 °C) to the mass spectrometer. Ion mobility separation resolved spectral overlap of peptide ions and significantly improved the detection of multiply charged species. The images acquired were of pixel size 100 µm (rat brain) and 50 µm (mouse brain), respectively. Observed tryptic peptides were filtered against proteomic target lists, generated by LC-MS, enabling tentative protein assignment for each peptide ion image. Precise localizations of peptide ions identified by DESI and MALDI were found to be comparable. Some spatially localized peptides ions were observed in DESI that were not found in the MALDI replicates, typically, multiply charged species with a low mass to charge ratio. This method demonstrates the potential of DESI-MSI to detect large numbers of tryptic peptides from tissue sections with enhanced spatial resolution when compared to previous DESI-MSI studies.

A Module for Analyzing Interactomes via APEX-MS Integrated into PatternLab for Proteomics.

Proximity labeling techniques, such as APEX-MS, provide valuable insights into proximal interactome mapping; however, the verification of biotinylated peptides is not straightforward. With this as motivation, we present a new module integrated into PatternLab for proteomics to enable APEX-MS data interpretation by targeting diagnostic fragment ions associated with APEX modifications. We reanalyzed a previously published APEX-MS data set and report a significant number of biotinylated peptides and, consequently, a confident set of proximal proteins. As the module is part of the widely adopted PatternLab for proteomics software suite, it offers users a comprehensive, easy, and integrated solution for data analysis. Given the broad utility of the APEX-MS technique in various biological contexts, we anticipate that our module will be a valuable asset to researchers, facilitating and enhancing interactome studies. PatternLab's APEX, including a usage protocol, is available at http://patternlabforproteomics.org/apex.

Marine-Derived Peptides with Anti-Hypertensive Properties: Prospects for Pharmaceuticals, Supplements, and Functional Food.

Hypertension, a major health concern linked to heart disease and premature mortality, has prompted a search for alternative treatments due to side effects of existing medications. Sustainable harvesting of low-trophic marine organisms not only enhances food security but also provides a variety of bioactive molecules, including peptides. Despite comprising only a fraction of active natural compounds, peptides are ideal for drug development due to their size, stability, and resistance to degradation. Our review evaluates the anti-hypertensive properties of peptides and proteins derived from selected marine invertebrate phyla, examining the various methodologies used and their application in pharmaceuticals, supplements, and functional food. A considerable body of research exists on the anti-hypertensive effects of certain marine invertebrates, yet many species remain unexamined. The array of assessments methods, particularly for ACE inhibition, complicates the comparison of results. The dominance of in vitro and animal in vivo studies indicates a need for more clinical research in order to transition peptides into pharmaceuticals. Our findings lay the groundwork for further exploration of these promising marine invertebrates, emphasizing the need to balance scientific discovery and marine conservation for sustainable resource use.

Python workflow for the selection and identification of marker peptides-proof-of-principle study with heated milk.

The analysis of almost holistic food profiles has developed considerably over the last years. This has also led to larger amounts of data and the ability to obtain more information about health-beneficial and adverse constituents in food than ever before. Especially in the field of proteomics, software is used for evaluation, and these do not provide specific approaches for unique monitoring questions. An additional and more comprehensive way of evaluation can be done with the programming language Python. It offers broad possibilities by a large ecosystem for mass spectrometric data analysis, but needs to be tailored for specific sets of features, the research questions behind. It also offers the applicability of various machine-learning approaches. The aim of the present study was to develop an algorithm for selecting and identifying potential marker peptides from mass spectrometric data. The workflow is divided into three steps: (I) feature engineering, (II) chemometric data analysis, and (III) feature identification. The first step is the transformation of the mass spectrometric data into a structure, which enables the application of existing data analysis packages in Python. The second step is the data analysis for selecting single features. These features are further processed in the third step, which is the feature identification. The data used exemplarily in this proof-of-principle approach was from a study on the influence of a heat treatment on the milk proteome/peptidome.

Cyanopeptides occurrence and diversity in a Brazilian tropical reservoir: Exploring relationships with water quality.

Microcystins (MCs) are a class of toxic secondary metabolites produced by some cyanobacteria strains that endanger aquatic and terrestrial organisms in various freshwater systems. Although patterns in MC occurrence are being recognized, divergences in the global data still hamper our ability to predict the toxicity of cyanobacterial blooms. This study aimed (i) to determine the dynamics of MCs and other cyanopeptides in a tropical reservoir, (ii) to investigate the correlation between peptides and potential cyanotoxin producers (iii) identifying the possible abiotic factors that influence the peptides. We analyzed, monthly, eight MC variants (MC-RR, -LA, -LF, -LR, -LW, -YR, [D-Asp3]-RR and [D-Asp3]-LR) and other peptides in 47 water samples collected monthly, all season long, from two sampling sites in a tropical eutrophic freshwater reservoir, in southeastern Brazil. The cyanopeptides were assessed by liquid chromatography-tandem mass spectrometry (LC-MS/MS). The biomass of potential cyanobacterial producers and water quality variables were measured. MCs were detected in both sampling sites year-round; the total MC concentration varied from 0.21 to 4.04 µg L-1, and three MC variants were identified and quantified (MC-RR, [D-Asp3]-RR, -LR). Additionally, we identified 28 compounds belonging to three other cyanopeptide classes: aeruginosin, microginin, and cyanopeptolin. As potential MC producers, Microcystis spp. and Dolichospermum circinalis were dominant during the study, representing up to 75% of the total phytoplankton. Correlational and redundancy analysis suggested positive effects of dissolved oxygen, nitrate, and total phosphorus on MC and microginins concentration, while water temperature appeared to favor aeruginosins. A comparison between our results and historical data showed a reduction in total phosphorus and cyanobacteria, suggesting increased water quality in the reservoir. However, the current MC concentrations indicate a rise in cyanobacterial toxicity over the last eight years. Moreover, our study underscores the pressing need to explore cyanopeptides other than MCs in tropical aquatic systems.