Coupling MALDI-TOF mass spectrometry protein and specialized metabolite analyses to rapidly discriminate bacterial function

SERS-based approaches in the investigation of bacterial metabolism, antibiotic resistance, and species identification

Surface-enhanced Raman scattering (SERS) is an inelastic scattering phenomenon that occurs when photons interact with substances, providing detailed molecular structure information. It exhibits various advantages including high sensitivity, specificity, and multiple-detection capabilities, which make it particularly effective in bacterial detection and antibiotic resistance research. In this review, we review the recent development of SERS-based approaches in the investigation of bacterial metabolism, antibiotic resistance, and species identification. Although the promising applications have been realized in clinical microbiology and diagnostics, several challenges still limit the further development, including signal variability, the complexity of spectral data interpretation, and the lack of standardized protocols. To overcome these obstacles, more reproducible and standardized methodologies, particularly in nanomaterial design and experimental condition optimization. Furthermore, the integration of SERS with machine learning and artificial intelligence can automate spectral analysis, improving the efficiency and accuracy of bacterial species identification, resistance marker detection, and metabolic monitoring. Combining SERS with other analytical techniques, such as mass spectrometry, fluorescence microscopy, or genomic sequencing, could provide a more comprehensive understanding of bacterial physiology and resistance mechanisms. As SERS technology advances, its applications are expected to extend beyond traditional microbiology to areas like environmental monitoring, food safety, and personalized medicine. In particular, the potential for SERS to be integrated into point-of-care diagnostic devices offers significant promise for enhancing diagnostics in resource-limited settings, providing cost-effective, rapid, and accessible solutions for bacterial infection and resistance detection.

Identification of Virulence Genes and Antibiotic Resistance in Extraintestinal Pathogenic Escherichia coli Isolated from Broiler Carcasses Using MALDI-TOF MS

Escherichia coli contamination in poultry is a significant concern due to its potential to cause foodborne illness. The presence of extraintestinal pathogenic E. coli (ExPEC) strains in chicken carcasses can lead to severe human infections. This study investigates the prevalence, virulence, and antibiotic resistance of E. coli isolates from chicken carcasses processed in both wet market and industrial environments, with a focus on the detection capabilities of MALDI-TOF MS. A total of 119 E. coli isolates were obtained. Only a small proportion (5/119) carried enteropathogenic virulence genes. In contrast, 71.42% (85/119) of the isolates harbored multiple extraintestinal virulence genes. Among these, iucC and sitA, which are associated with systemic infections, were present in 68.24% (58/85) and 43.53% (37/85) of the isolates, respectively. Furthermore, 47.06% (56/119) of the isolates carrying at least two extraintestinal virulence genes were classified as ExPEC. Additionally, 94.6% (54/56) of ExPEC isolates were multidrug resistant (MDR), showing resistance to over three antibiotic classes, raising concerns about the spread of antibiotic resistance. MALDI-TOF MS profiling revealed significant heterogeneity among the ExPEC isolates, with no distinct clustering patterns based on processing environment or sampling site. These findings underscore the public health risks posed by ExPEC in poultry and emphasize the need for improved surveillance, stringent hygiene practices, and responsible antibiotic use in poultry production.

Genome diversity, population structure and MALDI-TOF MS profiling of Aspergillus oryzae/flavus strains from fermentation and wild environments

Various strains of Aspergillus oryzae, regarded as a domesticated variant of aflatoxigenic Aspergillus flavus, are utilized in the soybean fermentation industry of Korea. This study compared A. oryzae/flavus strains isolated from various environments in Korea including industrial settings, Meju (brick of dried fermented soybeans), and wild conditions with globally reported strains using genomic analysis to determine their taxonomic positions and risk of mycotoxicity. Using population genomics, five distinct groups (A to E) were identified, with all aflatoxigenic Korean strains in Group C and non-aflatoxigenic Korean strains in Groups A, B, and E. Korean strains from Meju and wild conditions are distributed across Groups A and B, and most of the Korean industrial strains form a sub-cluster with Japanese industrial strains in Group A. Comparing secondary metabolite gene cluster mutation pattern, three gene clusters (Aflatoxin, Cyclopiazonic acid and Ditryptophenaline) were revealed as group specific ones. In aflatoxin and cyclopiazonic acid clusters, most of the Group C strains had intact regions compared to strains in other groups. Since most of the Group C strains produce aflatoxin and have intact Aflatoxin and Cyclopiazonic acid gene clusters, we considered that this group represent A. flavus. Profiling using MALDI-TOF MS analysis also distinguished Group C from Groups A, B and E by specific three proteomic peaks. Among the three peaks, those around 12,700 to 12,900 m/z (Da) are expected to correspond to AflF (nor B), an enzyme involved in Aflatoxin metabolism. These results showed taxonomic positions of Korean strains of A. oryzae/flavus from various environments and also showed possibility to differentiate between A. oryzae and A. flavus with genome and MALDI-TOF MS analysis.

Rationally minimizing natural product libraries using mass spectrometry

Natural products are a critical source of novel chemotypes for drug discovery. However, the implementation of natural product extract libraries in high throughput screening is hampered by natural product structural redundancy and potential for bioactive re-discovery. This challenge and large library sizes drastically increase the time and cost during initial high throughput screens. To address these limitations, we developed a method that leverages liquid chromatography-tandem mass spectrometry spectral similarity to dramatically reduce natural product library size, with minimal bioactive loss, and applied this to a collection of fungal extracts. Importantly, this method also afforded increased bioassay hit rates against microbial targets, with broad applicability across assays and natural product sources. Thus, this method offers a broadly applicable strategy for accelerated and cost-effective natural product drug discovery.

IMPORTANCE

Natural product libraries are large collections of extracts derived from fungi, plants, bacteria, or any other natural sources. These libraries play an important role in the initial phases of drug discovery, providing the basis for bioassays against a target of interest. However, these collections often comprise thousands of extracts with sometimes overlapping chemical structures, which can result in a bottleneck in both time and costs for the initial phases of drug discovery. Here, we have developed a method that uses mass spectrometry to dramatically reduce the size of these libraries, with minimal tradeoffs and improved success rates in bioassays. Ultimately, this will speed up the process of bioactive candidate identification and isolation, and drug development overall.

Characterization of Honey Microbiome Using MALDI-TOF Mass Spectrometry and Physicochemical Study

Honey, a super-saturated solution produced by Apis mellifera, is well-known for its historical medicinal uses, as well as culinary applications. Comprising sugars, phenols, enzymes, and more, its complex composition contributes to its medicinal properties. The microbiome, dominated by spore-forming bacteria and yeasts, is also a crucial factor in the health benefit properties of honey. The identification of the microbiome of honeys contributes to a better understanding of their microbial landscape and health-benefit properties and is also relevant to the environmental aspect. Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) is emerging as a key tool for microbial identification, but challenges remain in ensuring accuracy under different conditions. This study focuses on developing optimal conditions for microbial isolation and culture, aiming to balance diversity and avoid negative effects on identification. It further has the objective of evaluating the influence of geographic and botanical factors on the composition and diversity of the honey microbiome.

Use of MALDI-TOF mass spectrometry and IDBac to mine for understudied bacterial genera from the environment

Bacterial natural products have greatly contributed to the global drug discovery effort. Further, the incorporation of understudied bacterial taxa into discovery pipelines remains a promising approach to supply much needed chemical diversity to this effort. Unfortunately, researchers lack rapid and efficient techniques to accomplish this. Here we present an approach that employs matrix-assisted laser desorption/ionization time of flight mass spectrometry (MALDI-TOF MS) and the bioinformatics platform IDBac to perform targeted isolation of understudied bacteria from environmental samples. A dendrogram of MS protein spectra from 479 unknown bacterial isolates was seeded with spectra from 50 characterized strains that represented target understudied genera. This method was highly effective at identifying representatives from target taxa, demonstrating an 86.3% success rate when an estimated genus level cutoff was implemented in the dendrogram. Overall, this study shows the potential of MALDI-MS/IDBac to mine environmental bacterial isolate collections for target taxa in high-throughput, particularly in the absence of proprietary software. It also provides a cost-effective alternative to morphology and gene-sequencing analyses that are typically used to guide identification and prioritization strategies from large bacterial isolate collections.

A new fusion strategy for rapid strain differentiation based on MALDI-TOF MS and Raman spectra

Typing of bacterial subspecies is urgently needed for the diagnosis and efficient treatment during disease outbreaks. Physicochemical spectroscopy can provide a rapid analysis but its identification accuracy is still far from satisfactory. Herein, a novel feature-extractor-based fusion-assisted machine learning strategy has been developed for high accuracy and rapid strain differentiation using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) and Raman spectroscopy. Based on this fusion approach, rapid and reliable identification and analysis can be performed within 24 hours. Validation on a panel of important pathogens comprising Staphylococcus aureus, Klebsiella pneumoniae, Escherichia coli, and Acinetobacter baumannii showed that the identification accuracies of k-nearest neighbors (KNNs), support vector machines (SVMs) and artificial neural networks (ANNs) were 100%. In particular, when benchmarked against a MALDI-TOF MS spectral dataset, the new approach improved the identification accuracy of Acinetobacter baumannii from 87.67% to 100%. This work demonstrates the effectiveness of combining MALDI-TOF MS and Raman spectroscopy fusion data in pathogenic bacterial subtyping.

Discovery of megapolipeptins by genome mining of a Burkholderiales bacteria collection

Burkholderiales bacteria have emerged as a promising source of structurally diverse natural products that are expected to play important ecological and industrial roles. This order ranks in the top three in terms of predicted natural product diversity from available genomes, warranting further genome sequencing efforts. However, a major hurdle in obtaining the predicted products is that biosynthetic genes are often 'silent' or poorly expressed. Here we report complementary strain isolation, genomics, metabolomics, and synthetic biology approaches to enable natural product discovery. First, we built a collection of 316 rhizosphere-derived Burkholderiales strains over the course of five years. We then selected 115 strains for sequencing using the mass spectrometry pipeline IDBac to avoid strain redundancy. After predicting and comparing the biosynthetic potential of each strain, a biosynthetic gene cluster that was silent in the native Paraburkholderia megapolitana and Paraburkholderia acidicola producers was cloned and activated by heterologous expression in a Burkholderia sp. host, yielding megapolipeptins A and B. Megapolipeptins are unusual polyketide, nonribosomal peptide, and polyunsaturated fatty acid hybrids that show low structural similarity to known natural products, highlighting the advantage of our Burkholderiales genomics-driven and synthetic biology-enabled pipeline to discover novel natural products.

Origin and characterization of cyclodepsipeptides: Comprehensive structural approaches with focus on mass spectrometry analysis of alkali-cationized molecular species

Cyclodepsipeptides (CDPs) represent a huge family of chemically and structurally diverse molecules with a wide ability for molecular interactions. CDPs are cyclic peptide-related natural products made up of both proteinogenic and nonproteinogenic amino acids linked by amide and ester bonds. The combined use of different analytical methods is required to accurately determine their integral structures including stereochemistry, thus allowing deeper insights into their often-intriguing bioactivities and their possible usefulness. Our goal is to present the various methods developed to accurately characterize CDPs. Presently, Marfey's method and NMR (nuclear magnetic resonance) are still considered the best for characterizing CDP configuration. Nevertheless, electrospray-high resolution tandem mass spectrometry (ESI-HRMS/MS) is of great value for efficiently resolving CDP's composition and sequences. For instance, recent data shows that the fragmentation of cationized CDPs (e.g., [M + Li]+ and [M + Na]+) leads to selective cleavage of ester bonds and specific cationized product ions (b series) useful to get unprecedented sequence information. Thus, after a brief presentation of their structure, biological functions, and biosynthesis, we also provide a historic overview of these various analytical approaches as well as their advantages and limitations with a special emphasis on the emergence of methods based on HRMS/MS through recent fundamental works and applications.

Higher-order interactions and emergent properties of microbial communities: The power of synthetic ecology

Humans have long relied on microbial communities to create products, produce energy, and treat waste. The microbiota residing within our bodies directly impacts our health, while the soil and rhizosphere microbiomes influence the productivity of our crops. However, the complexity and diversity of microbial communities make them challenging to study and difficult to develop into applications, as they often exhibit the emergence of unpredictable higher-order phenomena. Synthetic ecology aims at simplifying complexity by constituting synthetic or semi-natural microbial communities with reduced diversity that become easier to study and analyze. This strategy combines methodologies that simplify existing complex systems (top-down approach) or build the system from its constituent components (bottom-up approach). Simplified communities are studied to understand how interactions among populations shape the behavior of the community and to model and predict their response to external stimuli. By harnessing the potential of synthetic microbial communities through a multidisciplinary approach, we can advance knowledge of ecological concepts and address critical public health, agricultural, and environmental issues more effectively.

Halomonas flagellata sp. nov., a halophilic bacterium isolated from saline soil in Xinjiang

A Gram-stain-negative, strictly aerobic, motile, slightly curved rod-shaped bacterium with multiple flagella, designated strain EGI 63088T, was isolated from a bulk soil of Kalidium foliatum, collected from Wujiaqu in Xinjiang Uighur Autonomous Region, PR China. The optimal growth temperature, salinity, and pH for strain EGI 63088T growth were 30 °C, 3% (w/v) NaCl and 8, respectively. Phylogenetic analysis using 16S rRNA gene sequences indicated that strain EGI 63088T showed the highest sequence similarities to Halomonas heilongjiangensis 9-2T (97.94%), H. lysinitropha 3(2)T (97.51%), and H. daqiaonensis CGMCC 1.9150T (97.08%). The average nucleotide identity and digital DNA-DNA hybridization values between the strain EGI 63088T and H. heilongjiangensis 9-2T were 89.03 and 41.10%, respectively. The DNA G + C content of the genome for strain EGI 63088T was 66.3 mol%. The most prevalent antibiotic resistance and virulence-related genes in Halomonas genomes were Streptomyces cinnamoneu EF-Tu mutant, pilT, and cheY, respectively. The predominant fatty acids of strain EGI 63088T were summed feature 8 (C18: 1 ω6c and/or C18: 1 ω7c), summed feature 3 (C16: 1 ω6c and/or C16: 1 ω7c), and C16: 0; its major respiratory quinone was ubiquinone-9 (Q-9), and the major polar lipids were diphosphatidylglycerol, phosphatidylglycerol, and phosphatidylethanolamine. According to the above results, strain EGI 63088T is considered a novel species of the genus Halomonas, for which the name Halomonas flagellata sp. nov. is proposed. The type strain is EGI 63088T (= KCTC 92047T = CGMCC 1.19133T).

Phomactinine, the First Nitrogen-Bearing Phomactin, Produced by Biatriospora sp. CBMAI 1333

Metabolomics analyses and improvement of growth conditions were applied toward diversification of phomactin terpenoids by the fungus Biatriospora sp. CBMAI 1333. Visualization of molecular networking results on Gephi assisted the observation of phomactin diversification and guided the isolation of new phomactin variants by applying a modified version of chemometrics based on a fractional factorial design. Consequentially, the first nitrogen-bearing phomactin, phomactinine (1), with a new rearranged carbon skeleton, was isolated and identified. The strategy combining metabolomics and chemometrics can be extended to include bioassay potency, structure novelty, and metabolic diversification connected or not to genomic analyses.

Discovery of a New Antibiotic Demethoxytetronasin Using a Dual-Sided Agar Plate Assay (DAPA)

For over a century, researchers have cultured microorganisms together on solid support─typically agar─in order to observe growth inhibition via antibiotic production. These simple bioassays have been critical to both academic researchers that study antibiotic production in microorganisms and to the pharmaceutical industry's global effort to discover drugs. Despite the utility of agar assays to researchers around the globe, several limitations have prevented their widespread adoption in advanced high-throughput compound discovery and dereplication campaigns. To address a list of specific shortcomings, we developed the dual-sided agar plate assay (DAPA), which exists in a 96-well plate format, allows microorganisms to compete through opposing sides of a solid support in individual wells, is amenable to high-throughput screening and automation, is reusable, and is low-cost. Herein, we validate the use of DAPA as a tool for drug discovery and show its utility to discover new antibiotic natural products. From the screening of 217 bacterial isolates on multiple nutrient media against 3 pathogens, 55 hits were observed, 9 known antibiotics were dereplicated directly from agar plugs, and a new antibiotic, demethoxytetronasin (1), was isolated from a Streptomyces sp. These results demonstrate that DAPA is an effective, accessible, and low-cost tool to screen, dereplicate, and prioritize bacteria directly from solid support in the front end of antibiotic discovery pipelines.

Metabolomics of bacterial-fungal pairwise interactions reveal conserved molecular mechanisms

Bacterial-fungal interactions (BFIs) can shape the structure of microbial communities, but the small molecules mediating these BFIs are often understudied. We explored various optimization steps for our microbial culture and chemical extraction protocols for bacterial-fungal co-cultures, and liquid chromatography-tandem mass spectrometry (LC-MS/MS) revealed that metabolomic profiles are mainly comprised of fungi derived features, indicating that fungi are the key contributors to small molecules in BFIs. LC-inductively coupled plasma MS (LC-ICP-MS) and MS/MS based dereplication using database searching revealed the presence of several known fungal specialized metabolites and structurally related analogues in these extracts, including siderophores such as desferrichrome, desferricoprogen, and palmitoylcoprogen. Among these analogues, a novel putative coprogen analogue possessing a terminal carboxylic acid motif was identified from Scopulariopsis sp. JB370, a common cheese rind fungus, and its structure was elucidated via MS/MS fragmentation. Based on these findings, filamentous fungal species appear to be capable of producing multiple siderophores with potentially different biological roles (i.e. various affinities for different forms of iron). These findings highlight that fungal species are important contributors to microbiomes via their production of abundant specialized metabolites and that elucidating their role in complex communities should continue to be a priority.

Fungal Endophytes: Microfactories of Novel Bioactive Compounds with Therapeutic Interventions; A Comprehensive Review on the Biotechnological Developments in the Field of Fungal Endophytic Biology over the Last Decade

The seminal discovery of paclitaxel from endophytic fungus Taxomyces andreanae was a milestone in recognizing the immense potential of endophytic fungi as prolific producers of bioactive secondary metabolites of use in medicine, agriculture, and food industries. Following the discovery of paclitaxel, the research community has intensified efforts to harness endophytic fungi as putative producers of lead molecules with anticancer, anti-inflammatory, antimicrobial, antioxidant, cardio-protective, and immunomodulatory properties. Endophytic fungi have been a valuable source of bioactive compounds over the last three decades. Compounds such as taxol, podophyllotoxin, huperzine, camptothecin, and resveratrol have been effectively isolated and characterized after extraction from endophytic fungi. These findings have expanded the applications of endophytic fungi in medicine and related fields. In the present review, we systematically compile and analyze several important compounds derived from endophytic fungi, encompassing the period from 2011 to 2022. Our systematic approach focuses on elucidating the origins of endophytic fungi, exploring the structural diversity and biological activities exhibited by these compounds, and giving special emphasis to the pharmacological activities and mechanism of action of certain compounds. We highlight the tremendous potential of endophytic fungi as alternate sources of bioactive metabolites, with implications for combating major global diseases. This underscores the significant role that fungi can play in the discovery and development of novel therapeutic agents that address the challenges posed by prevalent diseases worldwide.

Metabolomics of bacterial-fungal pairwise interactions reveal conserved molecular mechanisms

Bacterial-fungal interactions (BFIs) can shape the structure of microbial communities, but the small molecules mediating these BFIs are often understudied. We explored various optimization steps for our microbial culture and chemical extraction protocols for bacterial-fungal co-cultures, and liquid chromatography-tandem mass spectrometry (LC-MS/MS) revealed that metabolomic profiles are mainly comprised of fungi derived features, indicating that fungi are the key contributors to small molecule mediated BFIs. LC-inductively coupled plasma MS (LC-ICP-MS) and MS/MS based dereplication using database searching revealed the presence of several known fungal specialized metabolites and structurally related analogues in these extracts, including siderophores such as desferrichrome, desferricoprogen, and palmitoylcoprogen. Among these analogues, a novel putative coprogen analogue possessing a terminal carboxylic acid motif was identified from Scopulariopsis spp. JB370, a common cheese rind fungus, and its structure was elucidated via MS/MS fragmentation. Based on these findings, filamentous fungal species appear to be capable of producing multiple siderophores with potentially different biological roles (i.e. various affinities for different forms of iron). These findings highlight that fungal species are important contributors to microbiomes via their production of abundant specialized metabolites and their role in complex communities should continue to be a priority.

The Characterization and Beta-Lactam Resistance of Staphylococcal Community Recovered from Raw Bovine Milk

Staphylococci is an opportunistic bacterial population that is permanent in the normal flora of milk and poses a serious threat to animal and human health with some virulence factors and antibiotic-resistance genes. This study was aimed at identifying staphylococcal species isolated from raw milk and to determine hemolysis, biofilm, coagulase activities, and beta-lactam resistance. The raw milk samples were collected from the Düzce (Türkiye) region, and the study data represent a first for this region. The characterization of the bacteria was performed with MALDI-TOF MS and 16S rRNA sequence analysis. The presence of coa, icaB, blaZ, and mecA was investigated with PCR. A nitrocefin chromogenic assay was used for beta-lactamase screening. In this context, 84 staphylococci were isolated from 10 different species, and the dominant species was determined as S. aureus (32.14%). Although 32.14% of all staphylococci were positive for beta hemolysis, the icaB gene was found in 57.14%, coa in 46.42%, mecA in 15.47%, and blaZ in 8.33%. As a result, Staphylococcus spp. strains that were isolated from raw milk in this study contained some virulence factors at a high level, but also contained a relatively low level of beta-lactam resistance genes. However, considering the animal–environment–human interaction, it is considered that the current situation must be monitored constantly in terms of resistance concerns. It must not be forgotten that the development of resistance is in constant change among bacteria.

Enhancing chemical and biological diversity by co-cultivation

In natural product research, microbial metabolites have tremendous potential to provide new therapeutic agents since extremely diverse chemical structures can be found in the nearly infinite microbial population. Conventionally, these specialized metabolites are screened by single-strain cultures. However, owing to the lack of biotic and abiotic interactions in monocultures, the growth conditions are significantly different from those encountered in a natural environment and result in less diversity and the frequent re-isolation of known compounds. In the last decade, several methods have been developed to eventually understand the physiological conditions under which cryptic microbial genes are activated in an attempt to stimulate their biosynthesis and elicit the production of hitherto unexpressed chemical diversity. Among those, co-cultivation is one of the most efficient ways to induce silenced pathways, mimicking the competitive microbial environment for the production and holistic regulation of metabolites, and has become a golden methodology for metabolome expansion. It does not require previous knowledge of the signaling mechanism and genome nor any special equipment for cultivation and data interpretation. Several reviews have shown the potential of co-cultivation to produce new biologically active leads. However, only a few studies have detailed experimental, analytical, and microbiological strategies for efficiently inducing bioactive molecules by co-culture. Therefore, we reviewed studies applying co-culture to induce secondary metabolite pathways to provide insights into experimental variables compatible with high-throughput analytical procedures. Mixed-fermentation publications from 1978 to 2022 were assessed regarding types of co-culture set-ups, metabolic induction, and interaction effects.

Artificial intelligence in microbial natural product drug discovery: current and emerging role

Covering: up to the end of 2022Microorganisms are exceptional sources of a wide array of unique natural products and play a significant role in drug discovery. During the golden era, several life-saving antibiotics and anticancer agents were isolated from microbes; moreover, they are still widely used. However, difficulties in the isolation methods and repeated discoveries of the same molecules have caused a setback in the past. Artificial intelligence (AI) has had a profound impact on various research fields, and its application allows the effective performance of data analyses and predictions. With the advances in omics, it is possible to obtain a wealth of information for the identification, isolation, and target prediction of secondary metabolites. In this review, we discuss drug discovery based on natural products from microorganisms with the help of AI and machine learning.

Devosia ureilytica sp. nov., isolated from Kuche River in China

Two novel strains, designated XJ19-45^T and XJ19-1, were isolated from water of Kuche River in Xinjiang Uygur Autonomous Region, China. Their cells were Gram-stain-negative, aerobic and motile rods. The phylogenetic analyses based on 16S rRNA genes and genomes showed that the two isolates belonged to the genus Devosia and the closest relative was Devosia subaequoris HST3-14^T. The 16S rRNA genes sequences pairwise similarities, average nucleotide identities, digital DNA-DNA hybridizations and average amino acid identities between type strain XJ19-45^T and other relatives were all less than 98.3, 80.3, 23.6 and 85.7 %, respectively, all below the species delineation thresholds. Pan-genomic analysis indicated that the novel isolate XJ19-45^T shared 1594 core gene clusters with the 11 closely related type strains in Devosia, and the number of strain-specific clusters was 390. The major cellular fatty acids (>10 %) of the two isolates were summed feature 8, C_18 : 1 ω7c 11-methyl and C_16 : 0. Diphosphatidylglycerol, phosphatidylglycerol and glycolipids were the major polar lipids, and Q10 was the detected respiratory quinone. Based on the results of phenotypic, physiological, chemotaxonomic and genotypic characterizations, we propose that the isolates represent a novel species, for which the name Devosia ureilytica sp. nov. is proposed. The type strain is XJ19-45^T (=CGMCC 1.19388^T=KCTC 92263^T).

Rapid detection of Staphylococcus aureus and Streptococcus pneumoniae by real-time analysis of volatile metabolites

Early detection of pathogenic bacteria is needed for rapid diagnostics allowing adequate and timely treatment of infections. In this study, we show that secondary electrospray ionization–high resolution mass spectrometry (SESI-HRMS) can be used as a diagnostic tool for rapid detection of bacterial infections as a supportive system for current state-of-the-art diagnostics. Volatile organic compounds (VOCs) produced by growing S. aureus or S. pneumoniae cultures on blood agar plates were detected within minutes and allowed for the distinction of these two bacteria on a species and even strain level within hours. Furthermore, we obtained a fingerprint of clinical patient samples within minutes of measurement and predominantly observed a separation of samples containing live bacteria compared to samples with no bacterial growth. Further development of this technique may reduce the time required for microbiological diagnosis and should help to improve patient’s tailored treatment.

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Real-time mass spectrometry shows potential as a tool for microbiological diagnosis

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Bacterial volatile metabolites from 1 × 10³ CFUs are detected within minutes

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S. aureus and S. pneumoniae can be distinguished on species and even strain level

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Complex clinical samples cluster according to presence or absence of viable bacteria

Applications of MALDI-MS/MS-Based Proteomics in Biomedical Research

Matrix-assisted laser desorption/ionization (MALDI) mass spectrometry (MS) is one of the most widely used techniques in proteomics to achieve structural identification and characterization of proteins and peptides, including their variety of proteoforms due to post-translational modifications (PTMs) or protein-protein interactions (PPIs). MALDI-MS and MALDI tandem mass spectrometry (MS/MS) have been developed as analytical techniques to study small and large molecules, offering picomole to femtomole sensitivity and enabling the direct analysis of biological samples, such as biofluids, solid tissues, tissue/cell homogenates, and cell culture lysates, with a minimized procedure of sample preparation. In the last decades, structural identification of peptides and proteins achieved by MALDI-MS/MS helped researchers and clinicians to decipher molecular function, biological process, cellular component, and related pathways of the gene products as well as their involvement in pathogenesis of diseases. In this review, we highlight the applications of MALDI ionization source and tandem approaches for MS for analyzing biomedical relevant peptides and proteins. Furthermore, one of the most relevant applications of MALDI-MS/MS is to provide "molecular pictures", which offer in situ information about molecular weight proteins without labeling of potential targets. Histology-directed MALDI-mass spectrometry imaging (MSI) uses MALDI-ToF/ToF or other MALDI tandem mass spectrometers for accurate sequence analysis of peptide biomarkers and biological active compounds directly in tissues, to assure complementary and essential spatial data compared with those obtained by LC-ESI-MS/MS technique.

“Omic” Approaches to Bacteria and Antibiotic Resistance Identification

The quick and accurate identification of microorganisms and the study of resistance to antibiotics is crucial in the economic and industrial fields along with medicine. One of the fastest-growing identification methods is the spectrometric approach consisting in the matrix-assisted laser ionization/desorption using a time-of-flight analyzer (MALDI-TOF MS), which has many advantages over conventional methods for the determination of microorganisms presented. Thanks to the use of a multiomic approach in the MALDI-TOF MS analysis, it is possible to obtain a broad spectrum of data allowing the identification of microorganisms, understanding their interactions and the analysis of antibiotic resistance mechanisms. In addition, the literature data indicate the possibility of a significant reduction in the time of the sample preparation and analysis time, which will enable a faster initiation of the treatment of patients. However, it is still necessary to improve the process of identifying and supplementing the existing databases along with creating new ones. This review summarizes the use of “-omics” approaches in the MALDI TOF MS analysis, including in bacterial identification and antibiotic resistance mechanisms analysis.

Clay chips and beads capture in situ barley root microbiota and facilitate in vitro long-term preservation of microbial strains

Capturing the diverse microbiota from healthy and/or stress resilient plants for further preservation and transfer to unproductive and pathogen overloaded soils, might be a tool to restore disturbed plant-microbe interactions. Here, we introduce Aswan Pink Clay as a low-cost technology for capturing and storing the living root microbiota. Clay chips were incorporated into the growth milieu of barley plants and developed under gnotobiotic conditions, to capture and host the rhizospheric microbiota. Afterward, it was tested by both a culture-independent (16S rRNA gene metabarcoding) and -dependent approach. Both methods revealed no significant differences between roots and adjacent clay chips in regard total abundance and structure of the present microbiota. Clay shaped as beads adequately supported the long-term preservation of viable pure isolates of typical rhizospheric microbes, i.e. Bacillus circulans, Klebsiella oxytoca, Sinorhizobium meliloti, and Saccharomyces sp., up to 11 months stored at -20°C, 4°C, and ambient temperature. The used clay chips and beads have the capacity to capture the root microbiota and to long-term preserve pure isolates. Hence, the developed approach is qualified to build on it a comprehensive strategy to transfer and store complex and living environmental microbiota of rhizosphere toward biotechnological application in sustainable plant production and environmental rehabilitation.

Automated Microbial Library Generation Using the Bioinformatics Platform IDBac

Libraries of microorganisms have served as a cornerstone of therapeutic drug discovery, though the continued re-isolation of known natural product chemical entities has remained a significant obstacle to discovery efforts. A major contributing factor to this redundancy is the duplication of bacterial taxa in a library, which can be mitigated through the use of a variety of DNA sequencing strategies and/or mass spectrometry-informed bioinformatics platforms so that the library is created with minimal phylogenetic, and thus minimal natural product overlap. IDBac is a MALDI-TOF mass spectrometry-based bioinformatics platform used to assess overlap within collections of environmental bacterial isolates. It allows environmental isolate redundancy to be reduced while considering both phylogeny and natural product production. However, manually selecting isolates for addition to a library during this process was time intensive and left to the researcher's discretion. Here, we developed an algorithm that automates the prioritization of hundreds to thousands of environmental microorganisms in IDBac. The algorithm performs iterative reduction of natural product mass feature overlap within groups of isolates that share high homology of protein mass features. Employing this automation serves to minimize human bias and greatly increase efficiency in the microbial strain prioritization process.

Strategies to access biosynthetic novelty in bacterial genomes for drug discovery

Bacteria provide a rich source of natural products with potential therapeutic applications, such as novel antibiotic classes or anticancer drugs. Bioactivity-guided screening of bacterial extracts and characterization of biosynthetic pathways for drug discovery is now complemented by the availability of large (meta)genomic collections, placing researchers into the postgenomic, big-data era. The progress in next-generation sequencing and the rise of powerful computational tools provide unprecedented insights into unexplored taxa, ecological niches and 'biosynthetic dark matter', revealing diverse and chemically distinct natural products in previously unstudied bacteria. In this Review, we discuss such sources of new chemical entities and the implications for drug discovery with a particular focus on the strategies that have emerged in recent years to identify and access novelty.

Relationship between bacterial phylotype and specialized metabolite production in the culturable microbiome of two freshwater sponges

Microbial drug discovery programs rely heavily on accessing bacterial diversity from the environment to acquire new specialized metabolite (SM) lead compounds for the therapeutic pipeline. Therefore, knowledge of how commonly culturable bacterial taxa are distributed in nature, in addition to the degree of variation of SM production within those taxa, is critical to informing these front-end discovery efforts and making the overall sample collection and bacterial library creation process more efficient. In the current study, we employed MALDI-TOF mass spectrometry and the bioinformatics pipeline IDBac to analyze diversity within phylotype groupings and SM profiles of hundreds of bacterial isolates from two Eunapius fragilis freshwater sponges, collected 1.5 km apart. We demonstrated that within two sponge samples of the same species, the culturable bacterial populations contained significant overlap in approximate genus-level phylotypes but mostly nonoverlapping populations of isolates when grouped lower than the level of genus. Further, correlations between bacterial phylotype and SM production varied at the species level and below, suggesting SM distribution within bacterial taxa must be analyzed on a case-by-case basis. Our results suggest that two E. fragilis freshwater sponges collected in similar environments can exhibit large culturable diversity on a species-level scale, thus researchers should scrutinize the isolates with analyses that take both phylogeny and SM production into account to optimize the chemical space entering into a downstream bacterial library.

Mass spectrometry-based metabolomics in microbiome investigations

Microbiotas are a malleable part of ecosystems, including the human ecosystem. Microorganisms affect not only the chemistry of their specific niche, such as the human gut, but also the chemistry of distant environments, such as other parts of the body. Mass spectrometry-based metabolomics is one of the key technologies to detect and identify the small molecules produced by the human microbiota, and to understand the functional role of these microbial metabolites. This Review provides a foundational introduction to common forms of untargeted mass spectrometry and the types of data that can be obtained in the context of microbiome analysis. Data analysis remains an obstacle; therefore, the emphasis is placed on data analysis approaches and integrative analysis, including the integration of microbiome sequencing data.

Evolution of Diagnostic Methods for Helicobacter pylori Infections: From Traditional Tests to High Technology, Advanced Sensitivity and Discrimination Tools

Rapid diagnosis and treatment application in the early stages of H. pylori infection plays an important part in inhibiting the transmission of this infection as this bacterium is involved in various gastric pathologies such as gastritis, gastro-duodenal ulcer, and even gastric neoplasia. This review is devoted to a quick overview of conventional and advanced detection techniques successfully applied to the detection of H. pylori in the context of a compelling need to upgrade the standards of the diagnostic methods which are currently being used. Selecting the best diagnostic method implies evaluating different features, the use of one or another test depending on accessibility, laboratories equipment, and the clinical conditions of patients. This paper aims to expose the diagnosis methods for H. pylori that are currently available, highlighting their assets and limitations. The perspectives and the advantages of nanotechnology along with the concept of nano(bio)sensors and the development of lab-on-chip devices as advanced tools for H. pylori detection, differentiation, and discrimination is also presented, by emphasizing multiple advantages: simple, fast, cost-effective, portable, miniaturized, small volume of samples required, highly sensitive, and selective. It is generally accepted that the development of intelligent sensors will completely revolutionize the acquisition procedure and medical decision in the framework of smart healthcare monitoring systems.

Holistic Characterization of a Salmonella Typhimurium Infection Model Using Integrated Molecular Imaging

A more complete and holistic view on host-microbe interactions is needed to understand the physiological and cellular barriers that affect the efficacy of drug treatments and allow the discovery and development of new therapeutics. Here, we developed a multimodal imaging approach combining histopathology with mass spectrometry imaging (MSI) and same section imaging mass cytometry (IMC) to study the effects of Salmonella Typhimurium infection in the liver of a mouse model using the S. Typhimurium strains SL3261 and SL1344. This approach enables correlation of tissue morphology and specific cell phenotypes with molecular images of tissue metabolism. IMC revealed a marked increase in immune cell markers and localization in immune aggregates in infected tissues. A correlative computational method (network analysis) was deployed to find metabolic features associated with infection and revealed metabolic clusters of acetyl carnitines, as well as phosphatidylcholine and phosphatidylethanolamine plasmalogen species, which could be associated with pro-inflammatory immune cell types. By developing an IMC marker for the detection of Salmonella LPS, we were further able to identify and characterize those cell types which contained S. Typhimurium.

Artificial intelligence-guided discovery of anticancer lead compounds from plants and associated microorganisms

Plants and associated microorganisms are essential sources of natural products against human cancer diseases, partly exemplified by plant-derived anticancer drugs such as Taxol (paclitaxel). Natural products provide diverse mechanisms of action and can be used directly or as prodrugs for further anticancer optimization. Despite the success, major bottlenecks can delay anticancer lead discovery and implementation. Recent advances in sequencing and omics-related technology have provided a mine of information for developing new therapeutics from natural products. Artificial intelligence (AI), including machine learning (ML), has offered powerful techniques for extensive data analysis and prediction-making in anticancer leads discovery. This review presents an overview of current AI-guided solutions to discover anticancer lead compounds, focusing on natural products from plants and associated microorganisms.

Current Scenario and Challenges in the Direct Identification of Microorganisms Using MALDI TOF MS

MALDI TOF MS-based microbial identification significantly lowers the operational costs because of minimal requirements of substrates and reagents for extraction. Therefore, it has been widely used in varied applications such as clinical, food, military, and ecological research. However, the MALDI TOF MS method is laced with many challenges including its limitation of the reference spectrum. This review briefly introduces the background of MALDI TOF MS technology, including sample preparation and workflow. We have primarily discussed the application of MALDI TOF MS in the identification of microorganisms. Furthermore, we have discussed the current trends for bioaerosol detection using MALDI TOF MS and the limitations and challenges involved, and finally the approaches to overcome these challenges.

Capnocytophaga periodontitidis sp. nov., isolated from subgingival plaque of periodontitis patient

Two carbon dioxide-requiring, gliding, Gram-stain-negative strains, designated p1a2^T and 051621, were isolated from subgingival plaque in association with severe periodontitis. The 16S rRNA gene sequence analysis revealed that they represented members of the genus Capnocytophaga and had less than 96.4 % pairwise similarity with species with validly published names in this genus. The whole-genome sequences of those strains had less than 91.9 % average nucleotide identity and 48.4 % digital DNA-DNA hybridization values with the other type strains of species of the genus Capnocytophaga, both below the species delineation threshold. The results of pan-genomic analysis indicated that p1a2^T and 051621 shared 765 core gene families with the other ten species in this genus, and the numbers of strain-specific gene families were 493 and 455, respectively. The major fatty acids were iso-C_15 : 0 and C_16 : 0. A combination of phenotypic, chemotaxonomic, phylogenetic and genotypic data clearly indicate that p1a2^T and 051621 should be considered to represent a novel species of the genus Capnocytophaga, for which the name Capnocytophaga periodontitidis sp. nov. is proposed. The type strain is p1a2^T (=CGMCC 1.17337^T=JCM 34126^T).

Development of an inexpensive matrix-assisted laser desorption-time of flight mass spectrometry method for the identification of endophytes and rhizobacteria cultured from the microbiome associated with maize

Many endophytes and rhizobacteria associated with plants support the growth and health of their hosts. The vast majority of these potentially beneficial bacteria have yet to be characterized, in part because of the cost of identifying bacterial isolates. Matrix-assisted laser desorption-time of flight (MALDI-TOF) has enabled culturomic studies of host-associated microbiomes but analysis of mass spectra generated from plant-associated bacteria requires optimization. In this study, we aligned mass spectra generated from endophytes and rhizobacteria isolated from heritage and sweet varieties of Zea mays. Multiple iterations of alignment attempts identified a set of parameters that sorted 114 isolates into 60 coherent MALDI-TOF taxonomic units (MTUs). These MTUs corresponded to strains with practically identical (>99%) 16S rRNA gene sequences. Mass spectra were used to train a machine learning algorithm that classified 100% of the isolates into 60 MTUs. These MTUs provided >70% coverage of aerobic, heterotrophic bacteria readily cultured with nutrient rich media from the maize microbiome and allowed prediction of the total diversity recoverable with that particular cultivation method. Acidovorax sp., Pseudomonas sp. and Cellulosimicrobium sp. dominated the library generated from the rhizoplane. Relative to the sweet variety, the heritage variety c ontained a high number of MTUs. The ability to detect these differences in libraries, suggests a rapid and inexpensive method of describing the diversity of bacteria cultured from the endosphere and rhizosphere of maize.

Direct MALDI-TOF profiling of gingival crevicular fluid sediments for periodontitis diagnosis

Periodontitis is a widespread stomatological disease and represents one of the main causes of tooth loss in adults. Traditional diagnosis of periodontitis relies on the judgment by professional periodontists that cannot reveal its progression at the early stage. In this work, we characterized the gingival crevicular fluid (GCF) sediments of patients with periodontitis and healthy volunteers by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). Potential protein biomarkers were selected based on the multivariate statistical analysis of the MALDI-TOF mass spectra, followed by liquid chromatography-tandem mass spectrometry (LC-MS/MS) identification. Twelve potential protein biomarkers were identified from 17 patients compared to 7 healthy volunteers, including 5 microbial proteins and 7 human proteins, indicating the microbial composition and host response components related to the etiology of periodontitis. The panel of biomarkers was then verified with the GCF samples of another 11 patients. The 12 biomarkers also showed potential value in the early diagnosis of periodontitis. This work developed a rapid assay to screen periodontitis among populations. It can be popularized to non-periodontal specialists such as community general practitioners, benefiting the early and accurate monitoring of periodontitis. The identification of the potential biomarkers can also help in the understanding of the pathogenesis of periodontitis.

The need to innovate sample collection and library generation in microbial drug discovery: a focus on academia

The question of whether culturable microorganisms will continue to be a viable source of new drug leads is inherently married to the strategies used to collect samples from the environment, the methods used to cultivate microorganisms from these samples, and the processes used to create microbial libraries. An academic microbial natural products (NP) drug discovery program with the latest innovative chromatographic and spectroscopic technology, high-throughput capacity, and bioassays will remain at the mercy of the quality of its microorganism source library. This viewpoint will discuss limitations of sample collection and microbial strain library generation practices. Additionally, it will offer suggestions to innovate these areas, particularly through the targeted cultivation of several understudied bacterial phyla and the untargeted use of mass spectrometry and bioinformatics to generate diverse microbial libraries. Such innovations have potential to impact downstream therapeutic discovery, and make its front end more informed, efficient, and less reliant on serendipity. This viewpoint is not intended to be a comprehensive review of contributing literature and was written with a focus on bacteria. Strategies to discover NPs from microbial libraries, including a variety of genomics and "OSMAC" style approaches, are considered downstream of sample collection and library creation, and thus are out of the scope of this viewpoint.

Biodiversity, Bioactivity, and Metabolites of High Desert Derived Oregonian Soil Bacteria

From arid, high desert soil samples collected near Bend, Oregon, 19 unique bacteria were isolated. Each strain was identified by 16S rRNA gene sequencing, and their organic extracts were tested for antibacterial and antiproliferative activities. Noteworthy, six extracts (30 %) exhibited strong inhibition resulting in less than 50 % cell proliferation in more than one cancer cell model, tested at 10 μg/mL. Principal component analysis (PCA) of LC/MS data revealed drastic differences in the metabolic profiles found in the organic extracts of these soil bacteria. In total, fourteen potent antibacterial and/or cytotoxic metabolites were isolated via bioactivity-guided fractionation, including two new natural products: a pyrazinone containing tetrapeptide and 7-methoxy-2,3-dimethyl-4H-chromen-4-one, as well as twelve known compounds: furanonaphthoquinone I, bafilomycin C1 and D, FD-594, oligomycin A, chloramphenicol, MY12-62A, rac-sclerone, isosclerone, tunicamycin VII, tunicamycin VIII, and (6S,16S)-anthrabenzoxocinone 1.264-C.

Azospirillum oleiclasticum sp. nov, a nitrogen-fixing and heavy oil degrading bacterium isolated from an oil production mixture of Yumen Oilfield

Two nitrogen-fixing and heavy oil degrading strains, designated RWY-5-1-1^T and ROY-1-1-2, were isolated from an oil production mixture from Yumen Oilfield in China. The 16S rRNA gene sequence showed they belong to Azospirillum and have less than 96.1 % pairwise similarity with each species in this genus. The average nucleotide identity and digital DNA-DNA hybridization values between them and other type strains of Azospirillum species were less than 75.69 % and 22.0 %, respectively, both below the species delineation threshold. Pan-genomic analysis showed that the novel isolate RWY-5-1-1^T shared 2145 core gene families with other type strains in Azospirillum, and the number of strain-specific gene families was 1623, almost two times more than the number known from other species. Furthermore, genes related to nitrogenase, hydrocarbon degradation and biosurfactant production were found in the isolates' genomes. Also, this strain was capable of reducing acetylene to ethylene at a rate of 22nmol ethylene h^-1 (10⁸ cells) and degrading heavy oil at a rate of 36.2 %. The major fatty acids and polar lipids were summed feature 8 (C_18:1ω7c/C_18:1ω6c), and phosphatidylethanolamine, diphosphatidylglycerol, phosphatidylglycerol, and phosphatidylcholine. Furthermore, a combination of phenotypic, chemotaxonomic, phylogenetic and genotypic data clearly indicated that strains RWY-5-1-1^T and ROY-1-1-2 represent a novel species, for which the name Azospirillum oleiclasticum sp. nov. is proposed. The type strain is RWY-5-1-1^T (=CGMCC 1.13426^T =KCTC 72259 ^T). Azospirillum novel strains with the ability of heavy oil degradation associated with the promotion of plant growth has never been reported to date.

Identification and dereplication of endophytic Colletotrichum strains by MALDI TOF mass spectrometry and molecular networking

The chemical diversity of biologically active fungal strains from 42 Colletotrichum, isolated from leaves of the tropical palm species Astrocaryum sciophilum collected in pristine forests of French Guiana, was investigated. The collection was first classified based on protein fingerprints acquired by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) correlated with cytotoxicity. Liquid chromatography coupled to high-resolution tandem mass spectrometry (LC-HRMS/MS) data from ethyl acetate extracts were acquired and processed to generate a massive molecular network (MN) using the MetGem software. From five Colletotrichum strains producing cytotoxic specialized metabolites, we predicted the occurrence of peptide and cytochalasin analogues in four of them by MN, including a similar ion clusters in the MN algorithm provided by MetGem software. Chemoinformatics predictions were fully confirmed after isolation of three pentacyclopeptides (cyclo(Phe-Leu-Leu-Leu-Val), cyclo(Phe-Leu-Leu-Leu-Leu) and cyclo(Phe-Leu-Leu-Leu-Ile)) and two cytochalasins (cytochalasin C and cytochalasin D) exhibiting cytotoxicity at the micromolar concentration. Finally, the chemical study of the last active cytotoxic strain BSNB-0583 led to the isolation of four colletamides bearing an identical decadienamide chain.

Integrated into Environmental Biofilm Chromobacterium vaccinii Survives Winter with Support of Bacterial Community

Chromobacterium species are common in tropical and subtropical zones in environmental samples according to numerous studies. Here, we describe an environmental case of resident Chromobacterium vaccinii in biofilms associated with Carex spp. roots in Moscow region, Russia (warm-summer humid continental climate zone). We performed broad characterization of individual properties as well as surrounding context for better understanding of the premise of C. vaccinii survival during the winter season. Genome properties of isolated strains propose some insights into adaptation to habit and biofilm mode of life, including social cheaters carrying ΔluxR mutation. Isolated C. vaccinii differs from previously described strains in some biochemical properties and some basic characteristics like fatty acid composition as well as unique genome features. Despite potential to modulate membrane fluidity and presence of several genes responsible for cold shock response, isolated C. vaccinii did not survive during exposure to 4 °C, while in the complex biofilm sample, it was safely preserved for at least half a year in vitro at 4 °C. The surrounding bacterial community within the same biofilm with C. vaccinii represented a series of psychrophilic bacterial species, which may share resistance to low temperatures with other species within biofilm and provide C. vaccinii an opportunity to survive during the cold winter season.

Applying a Chemogeographic Strategy for Natural Product Discovery from the Marine Cyanobacterium Moorena bouillonii

The tropical marine cyanobacterium Moorena bouillonii occupies a large geographic range across the Indian and Western Tropical Pacific Oceans and is a prolific producer of structurally unique and biologically active natural products. An ensemble of computational approaches, including the creation of the ORCA (Objective Relational Comparative Analysis) pipeline for flexible MS¹ feature detection and multivariate analyses, were used to analyze various M. bouillonii samples. The observed chemogeographic patterns suggested the production of regionally specific natural products by M. bouillonii. Analyzing the drivers of these chemogeographic patterns allowed for the identification, targeted isolation, and structure elucidation of a regionally specific natural product, doscadenamide A (1). Analyses of MS² fragmentation patterns further revealed this natural product to be part of an extensive family of herein annotated, proposed natural structural analogs (doscadenamides B–J, 2–10); the ensemble of structures reflect a combinatorial biosynthesis using nonribosomal peptide synthetase (NRPS) and polyketide synthase (PKS) components. Compound 1 displayed synergistic in vitro cancer cell cytotoxicity when administered with lipopolysaccharide (LPS). These discoveries illustrate the utility in leveraging chemogeographic patterns for prioritizing natural product discovery efforts.

Exploring the Diversity of Cysteine-Rich Natural Product Peptides via MS/MS Fingerprint Ions

Natural product extracts present inherently complex matrices in which the identification of novel bioactive peptide species is challenged by low-abundance masses and significant structural and sequence diversity. Additionally, discovery efforts often result in the re-identification of known compounds, where modifications derived in vivo or during sample handling may obscure true sequence identity. Herein, we identify mass spectral (MS²) "fingerprint" ions characteristic of cyclotides, a diverse and biologically active family of botanical cysteine-rich peptides, based on regions of high sequence homology. We couple mass shift analysis with MS² spectral fingerprint ions cross referenced with CyBase-a cyclotide database-to discern unique mass species in Viola communis extracts from mass species that are likely already characterized and those with common modifications. The approach is extended to a related class of cysteine-rich peptides, the trypsin inhibitors, using the characterized botanical species Lagenaria siceraria. Coupling the observation of highly abundant MS² ions with mass shift analysis, we identify a new set of small, highly disulfide-bound cysteine-rich L. siceraria peptides.

New Methodology for the Identification of Metabolites of Saccharides and Cyclitols by Off-Line EC-MALDI-TOF-MS

A combination of electrochemistry (EC) and matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (off-line EC-MALDI-TOF-MS) was applied for determination of the studied biologically active compounds (D-glucose, D-fructose, D-galactose, D-pinitol, L-chiro-inositol, and myo-inositol) and their possible electrochemical metabolites. In this work, boron-doped diamond electrode (BDD) was used as a working electrode. MALDI-TOF-MS experiments were carried out (both in positive and negative ion modes and using two matrices) to identify the structures of electrochemical products. This was one of the first applications of the EC system for the generation of electrochemical products produced from saccharides and cyclitols. Moreover, exploratory data analysis approaches (correlation networks, hierarchical cluster analysis, weighted plots) were used in order to present differences/similarities between the obtained spectra, regarding the class of analyzed compounds, ionization modes, and used matrices. This work presents the investigation and comparison of fragmentation patterns of sugars, cyclitols, and their respective products generated through the electrochemistry (EC) process.

hcapca: Automated Hierarchical Clustering and Principal Component Analysis of Large Metabolomic Datasets in R

Microbial natural product discovery programs face two main challenges today: rapidly prioritizing strains for discovering new molecules and avoiding the rediscovery of already known molecules. Typically, these problems have been tackled using biological assays to identify promising strains and techniques that model variance in a dataset such as PCA to highlight novel chemistry. While these tools have shown successful outcomes in the past, datasets are becoming much larger and require a new approach. Since PCA models are dependent on the members of the group being modeled, large datasets with many members make it difficult to accurately model the variance in the data. Our tool, hcapca, first groups strains based on the similarity of their chemical composition, and then applies PCA to the smaller sub-groups yielding more robust PCA models. This allows for scalable chemical comparisons among hundreds of strains with thousands of molecular features. As a proof of concept, we applied our open-source tool to a dataset with 1046 LCMS profiles of marine invertebrate associated bacteria and discovered three new analogs of an established anticancer agent from one promising strain.

Addition of insoluble fiber to isolation media allows for increased metabolite diversity of lab-cultivable microbes derived from zebrafish gut samples

There is a gap in measured microbial diversity when comparing genomic sequencing techniques versus cultivation from environmental samples in a laboratory setting. Standardized methods in artificial environments may not recapitulate the environmental conditions that native microbes require for optimal growth. For example, the intestinal tract houses microbes at various pH values as well as minimal oxygen and light environments. These microbes are also exposed to an atypical source of carbon: dietary fiber compacted in fecal matter. To investigate how the addition of insoluble fiber to isolation media could affect the cultivation of microbes from zebrafish intestines, an isolate library was built and analyzed using the bioinformatics pipeline IDBac. While all isolation media encouraged the growth of species from several phyla, the extent of growth was greater with the addition of fiber allowing for easier isolation. Furthermore, fiber addition altered the metabolism of the cultivated gut-derived microbes and induced the production of unique metabolites that were not produced when microbes were otherwise grown on standard isolation media. Addition of this inexpensive carbon source to the media supported the cultivation of a diverse community whose secondary metabolite production may more closely replicate their metabolite production in vivo.

Custom Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometric Database for Identification of Environmental Isolates of the Genus Burkholderia and Related Genera

Success of discovery programs for microbial natural products is dependent on quick and concise discrimination between isolates from diverse environments. However, laboratory isolation and identification of priority genera using current 16S rRNA PCR-based methods are both challenging and time-consuming. An emerging strategy for rapid isolate discrimination is protein fingerprinting via matrix-assisted laser desorption ionization (MALDI) mass spectrometry. Using our in-house environmental isolate repository, we have created a main spectral (MSP) library for the Bruker Biotyper MALDI mass spectrometer that contains 95 entries, including Burkholderia, Caballeronia, Paraburkholderia, and other environmentally related genera. The library creation required the acquisition of over 2,250 mass spectra, which were manually reviewed for quality control and consolidated into a single reference library using a commercial software platform. We tested the effectiveness of the reference library by analyzing 49 environmental isolate strains using two different sample preparation methods. Overall, this approach correctly identified all strains to the genus level provided that suitable reference spectra were present in the MSP library. In this study, we present a fast, accurate method for taxonomic assignment of environmentally derived bacteria from the order Burkholderiales, providing a valuable alternative to traditional PCR-based methods. The MSP library described in the manuscript is available for use.IMPORTANCE The Gram-negative proteobacterial order Burkholderiales has emerged as a promising source of novel natural products in recent years. This order includes the genus Burkholderia and the newly defined genera Caballeronia and Paraburkholderia However, development of this resource has been hampered by difficulties with rapid and selective isolation of Burkholderiales strains from the environment. Environmental metagenome sequencing has revealed that the potential for natural products is not evenly distributed throughout the microbial world. Thus, large but targeted microbial isolate libraries are needed to effectively explore the chemical potential of natural products. To study these organisms efficiently, methods to quickly identify isolates to the genus level are required. Matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) is already used in clinical settings to reliably identify unknown bacterial pathogens. We have adapted similar methodology using the MALDI Biotyper instrument to rapidly identify environmental isolates of Burkholderia, Caballeronia, and Paraburkholderia for downstream natural product discovery.