Insights Into Subspecies Discrimination Potentiality From Bacteria MALDI-TOF Mass Spectra by Using Data Mining and Diversity Studies

The exploration of dominant spoilage bacteria in blue mussels (Mytilus edulis) stored under different modified atmospheres by MALDI-TOF MS in combination with 16S rRNA sequencing

Few studies have addressed species-level identification of spoilage bacteria in blue mussels packed under modified atmospheres (MAs). We investigated the effect of MAs and seasons on the tentative species-level of dominant spoilage bacteria in blue mussels. Summer (s) and winter (w) blue mussels were stored at 4 °C in the atmospheres (%CO2/O2/N2): A40s (30/40/30), B60s (40/60/0), C60s (0/60/40), A40w (30/40/30), and D75w (25/75/0). In total, 122 culturable isolates were obtained at the final stage of shelf life, when mortality was high (56-100%) and total psychrotrophic bacteria counted >7 log CFU g-1. Biochemical properties were analyzed using gram reactions, catalase and oxidase activities, and salt tolerance tests. Culturable isolates were identified through matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) and 16 S rRNA gene sequence analysis. Spoilage potential tests were investigated by evaluating protease, lipase, and fermentation activities as well as gas and H2S production. The culturable isolates showed tolerance to varied salt concentrations. Psychromonas arctica, Pseudoalteromonas elyakovii, and Shewanella frigidimarina were dominating in specific MAs. Winter blue mussels resulted in a higher variation of spoilage bacteria, including S. frigidimarina, S. vesiculosa, S. polaris, Micrococcus luteus, Paeniglutamicibacter terrestris sp. nov., and Alteromonas sp.

Comparison of peaks in the matrix-assisted laser desorption ionization time-of-flight mass spectrometry spectra of Staphylococcus aureus grown on various blood agar plates

Matrix-assisted laser desorption ionization-time-of-flight mass spectrometry (MALDI-TOF MS) is routinely used for bacterial identification in clinical laboratories. Bacterial protein expression may differ according to their growth conditions, especially the culture medium composition. We aimed to study the peak variations of Staphylococcus aureus grown on various blood agar plates (BAP), especially phenol-soluble modulin-mec (PSM-mec) peak (m/z 2409) associated with mecA gene conferring methicillin resistance. Methicillin-resistant S. aureus (MRSA) ATCC 43300 and eight clinical MRSA isolates were cultured on various commercial BAPs including tryptic soy agar-based BAPs, Columbia agar-based BAP and in-house BAPs with the addition of yeast extract. Analysis of the MALDI-TOF peaks of S. aureus, cultured on various BAPs, revealed the peak intensities of low-molecular weight proteins to vary depending on the composition of BAPs, especially the presence or absence of yeast extract. Especially, the PSM-mec and delta-toxin peaks showed low intensity for S. aureus ATCC 43300 and clinical isolates. No significant differences were found in the number of peaks, but some peaks had lower intensity, corresponding to the medium containing yeast extract, in low-mass region (<m/z 4000). BAPs based on tryptic soy agar rather than Columbia agar seems to be appropriate for the detection of PSM-mec, a methicillin resistance marker of S. aureus and delta-toxin, an agr function indicator.

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.

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.

Using MALDI-TOF spectra in epidemiological surveillance for the detection of bacterial subgroups with a possible epidemic potential

Background

For the purpose of epidemiological surveillance, the Hospital University Institute Méditerranée infection has implemented since 2013 a system named MIDaS, based on the systematic collection of routine activity materials, including MALDI-TOF spectra, and results. The objective of this paper is to present the pipeline we use for processing MALDI-TOF spectra during epidemiological surveillance in order to disclose proteinic cues that may suggest the existence of epidemic processes in complement of incidence surveillance. It is illustrated by the analysis of an alarm observed for Streptococcus pneumoniae.

Methods

The MALDI-TOF spectra analysis process looks for the existence of clusters of spectra characterized by a double time and proteinic close proximity. This process relies on several specific methods aiming at contrasting and clustering the spectra, presenting graphically the results for an easy epidemiological interpretation, and for determining the discriminating spectra peaks with their possible identification using reference databases.

Results

The use of this pipeline in the case of an alarm issued for Streptococcus pneumoniae has made it possible to reveal a cluster of spectra with close proteinic and temporal distances, characterized by the presence of three discriminant peaks (5228.8, 5917.8, and 8974.3 m/z) and the absence of peak 4996.9 m/z. A further investigation on UniProt KB showed that peak 5228.8 is possibly an OxaA protein and that the absent peak may be a transposase.

Conclusion

This example shows this pipeline may support a quasi-real time identification and characterization of clusters that provide essential information on a potentially epidemic situation. It brings valuable information for epidemiological sensemaking and for deciding on the continuation of the epidemiological investigation, in particular the involving of additional costly resources to confirm or invalidate the alarm.

Clinical trials registration

NCT03626987.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12879-021-06803-3.

Consequences of the COVID-19 Outbreak Lockdown on Non-Viral Infectious Agents as Reported by a Laboratory-Based Surveillance System at the IHU Méditerranée Infection, Marseille, France

The objective of this paper is to describe the surveillance system MIDaS and to show how this system has been used for evaluating the consequences of the French COVID-19 lockdown on the bacterial mix of AP-HM and the antibiotic resistance. MIDas is a kind of surveillance activity hub, allowing the automatic construction of surveillance control boards. We investigated the diversity and resistance of bacterial agents from respiratory, blood, and urine samples during the lockdown period (from week 12 to 35 of 2020), using the same period of years from 2017 to 2019 as control. Taking into account the drop in patient recruitment, several species have exhibited significant changes in their relative abundance (either increasing or decreasing) with changes up to 9%. The changes were more important for respiratory and urine samples than for blood samples. The relative abundance in respiratory samples for the whole studied period was higher during the lockdown. A significant increase in the percentage of wild phenotypes during the lockdown was observed for several species. The use of the MIDaS syndromic collection and surveillance system made it possible to efficiently detect, analyze, and follow changes of the microbiological population as during the lockdown period.

Sputum proteomic analysis for distinguishing between pulmonary tuberculosis and non-tuberculosis using matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS): preliminary results

OBJECTIVES

The aim was to evaluate the feasibility and diagnostic contribution of protein profiling using matrix-assisted laser desorption ionization time-of-flight (MALDI-TOF) mass spectrometry (MS) applied to sputum to diagnose pulmonary tuberculosis.

METHODS

Sputum samples collected from patients suspected of having pulmonary tuberculosis were analysed using MALDI-TOF MS. Using the differentially expressed protein peaks, we compared three groups of patients, including those with confirmed pulmonary tuberculosis (PTB), those without tuberculosis but with a lower respiratory tract infection (non-TB LRTI) and those without tuberculosis and without an LRTI (non-TB controls).

RESULTS

A total of 102 patients included 35 PTB, 36 non-TB LRTI and 31 non-TB controls. The model differentiated between the PTB patients and the non-TB controls using the 25 most differentially expressed protein peaks, with a sensitivity of 97%, 95% CI 85-100%, and a specificity of 77%, 95% CI 59-90%. The model distinguished the PTB patients from the non-TB LRTI patients using the ten most differentially expressed protein peaks, with a sensitivity of 80%, 95% CI 63-92%, and a specificity of 89%, 95% CI 74-97%. We observed that the negative predictive value of MALDI-TOF MS sputum analysis was higher (96%, 95% CI 80-100%) than that of direct sputum microscopic examination and sputum culture (78%, 95% CI 62-89%) for non-TB controls. When MALDI-TOF MS sputum analysis and direct microscopic examination were combined, the negative predictive value reached 94%, 95% CI 80-99%, for non-TB LRTI patients.

DISCUSSION

These results suggest that MALDI-TOF MS sputum analysis coupled with microscopic examination could be used as a screening tool for diagnosing pulmonary TB.

Network Analysis Based on Unique Spectral Features Enables an Efficient Selection of Genomically Diverse Operational Isolation Units

Culturomics-based bacterial diversity studies benefit from the implementation of MALDI-TOF MS to remove genomically redundant isolates from isolate collections. We previously introduced SPeDE, a novel tool designed to dereplicate spectral datasets at an infraspecific level into operational isolation units (OIUs) based on unique spectral features. However, biological and technical variation may result in methodology-induced differences in MALDI-TOF mass spectra and hence provoke the detection of genomically redundant OIUs. In the present study, we used three datasets to analyze to which extent hierarchical clustering and network analysis allowed to eliminate redundant OIUs obtained through biological and technical sample variation and to describe the diversity within a set of spectra obtained from 134 unknown soil isolates. Overall, network analysis based on unique spectral features in MALDI-TOF mass spectra enabled a superior selection of genomically diverse OIUs compared to hierarchical clustering analysis and provided a better understanding of the inter-OIU relationships.