Identification of airborne bacteria by 16S rDNA sequencing, MALDI-TOF MS and the MIDI microbial identification system

Comparative genomic analyses of the genus Robertmurraya and proposal of the novel species Robertmurraya mangrovi sp. nov., isolated from mangrove soil

A Gram-positive, aerobic, motile, rod-shaped bacterial strain, designated 31A1RT, was isolated from the mangrove soil of Xilian village, Zhanjiang, China. Strain 31A1RT thrives at temperatures ranging from 15 to 45 °C (optimum at 30 °C), pH 6.5-10 (optimum at 8.5), and in the presence of 0-5% (w/v) NaCl (optimum at 1.5%). The strain shares the highest 16S rRNA gene sequence similarity with Robertmurraya crescens (97.24%) and Robertmurraya dakarensis (97.18%). The complete genome of strain 31A1RT spans 4.71 Mbp with a genomic DNA G + C content of 35.9 mol%. The average nucleotide identity and DNA-DNA hybridization values between strain 31A1RT and type strains of other species of the genus Robertmurraya were 71.24-72.11% and 19.90-21.40%, respectively. The amino acid identity values and percentage of conserved proteins ranged from 66.94 to 68.10% and from 58.34 to 61.62%, respectively, aligning with intrageneric cutoff values. The major fatty acids (≥ 5.0%) were iso-C14:0 (5.0%), iso-C15:0 (41.4%), iso-C16:0 (12.6%), C16:1ω7c alcohol (12.2%), and iso-C17:1 ω10c (6.5%). The polar lipids profile was mainly composed of diphosphatidyl glycerol, phosphatidyl glycerol, and phosphatidyl ethanolamine. We also profiled the pan-genome and metabolic features of genomic assemblies of strains belonging to the genus Robertmurraya, which indicated functional capacities and metabolic similarities. Consequently, we propose that strain 31A1RT represents a new species in the genus Robertmurraya, for which the name Robertmurraya mangrovi sp. nov. is proposed, with the type strain being 31A1RT (= GDMCC 1.4378T = JCM 36937T).

Saccharopolyspora mangrovi sp. nov., a novel mangrove soil actinobacterium with distinct metabolic potential revealed by comparative genomic analysis

A novel mangrove soil-derived actinomycete, strain S2-29T, was found to be most closely related to Saccharopolyspora karakumensis 5K548T based on 16 S rRNA sequence (99.24% similarity) and genomic phylogenetic analyses. However, significant divergence in digital DNA-DNA hybridization, average nucleotide identity, and unique biosynthetic gene cluster possession distinguished S2-29T as a distinct Saccharopolyspora species. Pan genome evaluation revealed exceptional genomic flexibility in genus Saccharopolyspora, with > 95% accessory genome content. Strain S2-29T harbored 718 unique genes, largely implicated in energetic metabolisms, indicating different metabolic capacities from its close relatives. Several uncharacterized biosynthetic gene clusters in strain S2-29T highlighted the strain's untapped capacity to produce novel functional compounds with potential biotechnological applications. Designation as novel species Saccharopolyspora mangrovi sp. nov. (type strain S2-29T = JCM 34,548T = CGMCC 4.7716T) was warranted, expanding the known Saccharopolyspora diversity and ecology. The discovery of this mangrove-adapted strain advances understanding of the genus while highlighting an untapped source of chemical diversity.

Comparison of MALDI-TOF mass spectrometry and 16S rDNA sequencing for identification of environmental bacteria: a case study of cave mussel-associated culturable microorganisms

Matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) is routinely used as a rapid and cost-effective method for pathogen identification in clinical settings. In comparison, its performance in other microbiological fields, such as environmental microbiology, is still being tested, although isolates of environmental microbes are essential for in-depth in vivo studies of their biology, including biotechnological applications. We investigated the applicability of MALDI-TOF MS for the identification of bacterial isolates from a highly oligotrophic environment - Dinaric Karst caves, which likely harbor specific microorganisms. We cultured bacteria from the shell surface of the endemic mussel Congeria jalzici, one of the three known cave mussels in the world that lives in the Dinaric karst underground. The bacterial isolates were obtained by swabbing the shell surface of mussels living in microhabitats with different amounts of water: 10 air-exposed mussels, 10 submerged mussels, and 10 mussels in the hygropetric zone. A collection of 87 pure culture isolates was obtained, mostly belonging to the phylum Bacillota (72%), followed by Pseudomonadota (16%), Actinomycetota (11%), and Bacteroidota (1%). We compared the results of MALDI-TOF MS identification (Bruker databases DB-5989 and version 11, v11) with the results of 16S rDNA-based phylogenetic analysis, a standard procedure for bacterial identification. Identification to the genus level based on 16S rDNA was possible for all isolates and clearly outperformed the results from MALDI-TOF MS, although the updated MALDI-TOF MS database v11 gave better results than the DB-5989 version (85% versus 62%). However, identification to the species-level by 16S rDNA sequencing was achieved for only 17% of isolates, compared with 14% and 40% for the MALDI-TOF MS databases DB-5989 and v11 database, respectively. In conclusion, our results suggest that continued enrichment of MALDI-TOF MS libraries will result with this method soon becoming a rapid, accurate, and efficient tool for assessing the diversity of culturable bacteria from different environmental niches.

A comprehensive review of microbial contamination in the indoor environment: sources, sampling, health risks, and mitigation strategies

The quality of the indoor environment significantly impacts human health and productivity, especially given the amount of time individuals spend indoors globally. While chemical pollutants have been a focus of indoor air quality research, microbial contaminants also have a significant bearing on indoor air quality. This review provides a comprehensive overview of microbial contamination in built environments, covering sources, sampling strategies, and analysis methods. Microbial contamination has various origins, including human occupants, pets, and the outdoor environment. Sampling strategies for indoor microbial contamination include air, surface, and dust sampling, and various analysis methods are used to assess microbial diversity and complexity in indoor environments. The review also discusses the health risks associated with microbial contaminants, including bacteria, fungi, and viruses, and their products in indoor air, highlighting the need for evidence-based studies that can relate to specific health conditions. The importance of indoor air quality is emphasized from the perspective of the COVID-19 pandemic. A section of the review highlights the knowledge gap related to microbiological burden in indoor environments in developing countries, using India as a representative example. Finally, potential mitigation strategies to improve microbiological indoor air quality are briefly reviewed.

Isolation, identification, and significance of salivary Veillonella spp., Prevotella spp., and Prevotella salivae in patients with inflammatory bowel disease

The global prevalence of inflammatory bowel disease (IBD) is on the rise, prompting significant attention from researchers worldwide. IBD entails chronic inflammatory disorders of the intestinal tract, characterized by alternating flares and remissions. Through high-throughput sequencing, numerous studies have unveiled a potential microbial signature for IBD patients showing intestinal enrichment of oral-associated bacteria. Simultaneously, the oral microbiome can be perturbed by intestinal inflammation. Our prior investigation, based on 16S rRNA amplicon sequencing, underscored elevated abundance of Veillonella spp. and Prevotella spp. in the salivary microbiomes of IBD patients. Noteworthy, Prevotella salivae emerged as a distinct species significantly associated with IBD. P. salivae is an under-recognized pathogen that was found to play a role in both oral and systemic diseases. In this study, we delve deeper into the salivary microbiomes of both IBD patients and healthy controls. Employing diverse cultivation techniques and real-time quantitative polymerase chain reactions (RT-qPCR), we gauged the prevalence and abundance of Veillonella spp., Prevotella spp., and P. salivae. Our isolation efforts yielded 407 and 168 strains of Veillonella spp., as well as 173 and 90 strains of Prevotella spp., from the saliva samples of IBD patients and healthy controls, respectively. Veillonella-vancomycin agar emerged as the discerning choice for optimal Veillonella spp. cultivation, while Schaedler kanamycin-vancomycin agar proved to be the most suitable medium for cultivating Prevotella spp. strains. Comparing our RT-qPCR findings to the previous 16S rRNA amplicon sequencing data, the results corroborated the higher abundance of Veillonella spp., Prevotella spp., and P. salivae in the saliva of IBD patients compared to healthy controls. However, it's worth noting that in contrast to RT-qPCR, the 16S rRNA amplicon sequencing data revealed greater absolute abundance of all three bacterial groups in both IBD patients and controls.

Airborne bacterial species in indoor air and association with physical factors

The aim of this study is to obtain knowledge about which cultivable bacterial species are present in indoor air in homes, and whether the concentration and diversity of airborne bacteria are associated with different factors. Measurements have been performed for one whole year inside different rooms in five homes and once in 52 homes. Within homes, a room-to-room variation for concentrations of airborne bacteria was found, but an overlap in bacterial species was found across rooms. Eleven species were found very commonly and included: Acinetobacter lowffii, Bacillus megaterium, B. pumilus, Kocuria carniphila, K. palustris, K. rhizophila, Micrococcus flavus, M. luteus, Moraxella osloensis and Paracoccus yeei. The concentrations of Gram-negative bacteria in general and the species P. yeei were significantly associated with the season with the highest concentrations in spring. The concentrations of P. yeei, K. rhizophila and B. pumilus were associated positively with relative humidity (RH), and concentrations of K. rhizophila were associated negatively with temperature and air change rate (ACR). Micrococcus flavus concentrations were associated negatively with ACR. Overall, this study identified species which are commonly present in indoor air in homes, and that the concentrations of some species were associated with the factors: season, ACR and RH.

Streptomonospora mangrovi sp. nov., isolated from mangrove soil showing similar metabolic capabilities, but distinct secondary metabolites profiles

A novel actinomycete, designated strain S1-112 ^T, was isolated from a mangrove soil sample from Hainan, China, and characterized using a polyphasic approach. Strain S1-112 ^T showed the highest similarity of the 16S rRNA gene to Streptomonospora nanhaiensis 12A09^T (99.24%). Their close relationship was further supported by phylogenetic analyses, which placed these two strains within a stable clade. The highest values of digital DNA-DNA hybridization (dDDH, 41.4%) and average nucleotide identity (ANI, 90.55%) were detected between strain S1-112 ^T and Streptomonospora halotolerans NEAU-Jh2-17 ^T. Genotypic and phenotypic characteristics demonstrated that strain S1-112 ^T could be distinguished from its closely related relatives. We also profiled the pan-genome and metabolic features of genomic assemblies of strains belonging to the genus Streptomonospora, indicating similar functional capacities and metabolic activities. However, all of these strains showed promising potential for producing diverse types of secondary metabolites. In conclusion, strain S1-112 ^T represents a novel species of the genus Streptomonospora, for which the name Streptomonospora mangrovi sp. nov. was proposed. The type strain is S1-112 ^T (= JCM 34292 ^T).

Limosilactobacillus walteri sp. nov., a novel probiotic antimicrobial lipopeptide-producing bacterium

A Gram-positive facultative anaerobe, nonspore forming, and nonmotile bacterial strain M31 was isolated from faecal contaminated soil. The strain is previously reported to produce a novel antimicrobial lipopeptide and displayed probiotic properties. The strain M31 is catalase negative and fermented d-galactose, d-glucose, esculin, d-maltose, d-lactose, d-melibiose, d-raffinose, d-saccharose (weak reaction), d-xylose (weak reaction), d-ribose (weak reaction), and l-arabinose (weak reaction). The majority of fatty acids were C16:0 (53.9%), C18:0 (26.9%), and C19:0 cyclo ω8c (19.1%). The genome is 2 234 040 bp long with 38.81% guanine-cytosine (GC) content. The pairwise ortho average nucleotide identity and digital DNA-DNA hybridization values of strain M31 with its closest relative species from Limosilactobacillus reuteri clade and Lm. rudii is below the recommended cut-off of 95% and 70%, respectively. Herein, we propose Lm. walteri sp. nov. as a novel species of the genus Limosilactobacillus with M31 = MTCC 12838 = JCM 32759 = KCTC 25569.

Culture-Independent Raman Spectroscopic Identification of Bacterial Pathogens from Clinical Samples Using Deep Transfer Learning

The rapid identification of bacterial pathogens in clinical samples like blood, urine, pus, and sputum is the need of the hour. Conventional bacterial identification methods like culturing and nucleic acid-based amplification have limitations like poor sensitivity, high cost, slow turnaround time, etc. Raman spectroscopy, a label-free and noninvasive technique, has overcome these drawbacks by providing rapid biochemical signatures from a single bacterium. Raman spectroscopy combined with chemometric methods has been used effectively to identify pathogens. However, a robust approach is needed to utilize Raman features for accurate classification while dealing with complex data sets such as spectra obtained from clinical isolates, showing high sample-to-sample heterogeneity. In this study, we have used Raman spectroscopy-based identification of pathogens from clinical isolates using a deep transfer learning approach at the single-cell level resolution. We have used the data-augmentation method to increase the volume of spectra needed for deep-learning analysis. Our ResNet model could specifically extract the spectral features of eight different pathogenic bacterial species with a 99.99% classification accuracy. The robustness of our model was validated on a set of blinded data sets, a mix of cultured and noncultured bacterial isolates of various origins and types. Our proposed ResNet model efficiently identified the pathogens from the blinded data set with high accuracy, providing a robust and rapid bacterial identification platform for clinical microbiology.

A systematic review of enteric pathogens and antibiotic resistance genes in outdoor urban aerosols

Aerosol transport of enteric microbiota including fecal pathogens and antimicrobial resistance genes (ARGs) has been documented in a range of settings but remains poorly understood outside indoor environments. We conducted a systematic review of the peer-reviewed literature to summarize evidence on specific enteric microbiota including enteric pathogens and ARGs that have been measured in aerosol samples in urban settings where the risks of outdoor exposure and antibiotic resistance (AR) spread may be highest. Following PRISMA guidelines, we conducted a key word search for articles published within the years 1990-2020 using relevant data sources. Two authors independently conducted the keyword searches of databases and conducted primary and secondary screenings before merging results. To be included, studies contained extractable data on enteric microbes and AR in outdoor aerosols regardless of source confirmation and reported on qualitative, quantitative, or viability data on enteric microbes or AR. Qualitative analyses and metric summaries revealed that enteric microbes and AR have been consistently reported in outdoor aerosols, generally via relative abundance measures, though gaps remain preventing full understanding of the role of the aeromicrobiological pathway in the fate and transport of enteric associated outdoor aerosols. We identified remaining gaps in the evidence base including a need for broad characterization of enteric pathogens in bioaerosols beyond bacterial genera, a need for greater sampling in locations of high enteric disease risk, and a need for quantitative estimation of microbial and nucleic acid densities that may be applied to fate and transport models and in quantitative microbial risk assessment.

Occultella gossypii sp. nov., an alkali-resistant isolate from soil sampled in a cotton field

A non-spore-forming, motile and alkali-resistant actinobacterium, designated N2-46T, was isolated from an alkaline soil sample collected from a cotton field in the Xinjiang region of PR China. Strain N2-46T formed creamy colonies on tryptone soy agar and managed to survive in extreme alkaline conditions at a pH value of 11. Strain N2-46T displayed the highest 16S rRNA gene similarity of 99.65 % to Haloactinobacterium kanbiaonis HY164T, followed by Occultella aeris F300T (99.61%) and Occultella glacieicola T3246-1T (98.54 %). 16S rRNA-directed phylogenetic analysis showed that strain N2-46T was embedded in a subclade with O. aeris F300T with a bootstrap value of 71.8 %. The phylogenetic tree based on core genes of genome sequences showed that strain N2-46T formed a unique subclade next to H. kanbiaonis HY164T and O. aeris F300T with a bootstrap value of 100 %. Digital DNA–DNA hybridization and the average nucleotide identity analyses showed that strain N2-46T displayed the highest values of 67.1 % (63.2–70.7 %) and 91.82 % with H. kanbiaonis HY164T, respectively. Comparative genomic analysis indicated that strain N2-46T and its three closest neighbours exhibited comparable distribution patterns in heavy metal resistance genes and biosynthetic gene clusters, while displaying distinctions probably related to ecological adaptation. MK-8(H4) was identified as the predominant isoprenoid quinone. The main fatty acids were identified as iso-C14 : 0 and anteiso-C15 : 0. Polar lipids are composed of diphosphatidylglycerol, phosphatidylglycerol, phosphatidylinositol, mono and diacylated phosphatidylinositol dimannosides, as well as several uncharacterized polar lipid, glycolipid, and phospholipids. Genotypic and physiological analyses support the view that strain N2-46T (=JCM 34413T=CGMCC 1.18819T) should be classified as a novel species of the genus Occultella , for which the name Occultella gossypii sp. nov. is proposed.

Halomonas sedimenti sp. nov., a Halotolerant Bacterium Isolated from Deep-Sea Sediment of the Southwest Indian Ocean

A Gram-staining-negative, aerobic, flagellated, motile, rod-shaped, halophilic bacterium QX-2^T was isolated from the deep-sea sediment of the Southwest Indian Ocean at a depth of 2699 m. Growth of the QX-2^T bacteria was observed at 4-50 °C (optimum 30 °C), pH 5.0-12.0 (optimum pH 6.0) and 0%-30% NaCl (w/v) [optimum 4% (w/v)]. 16S rRNA gene sequencing revealed that strain QX-2^T has the closest relationship with Halomonas titanicae DSM 22872^T (98.2%). Phylogeny analysis classified the strain QX-2^T into the genus Halomonas. The average nucleotide identity and DNA-DNA hybridization values between strain QX-2^T and related type strains were lower than the currently accepted new species definition standards. Principal fatty acids (> 10%) determined were C_16:0 (12.41%), C_12:0-3OH (25.15%), summed feature 3 (C_16:1 ω7c and/or C_16:1 ω6c, 11.55%) and summed feature 8 (C_18:1 ω7c and/or C_18:1 ω6c, 16.06%). Identified polar lipids in strain QX-2^T were diphosphatidylglycerol, phosphatidylglycerol, phosphatidylethanolamine, unidentified phospholipid, unidentified aminophospholipid and five unidentified lipids (L1-L5). The main respiratory quinone was Q-9. The content of DNA G+C was determined to be 54.34 mol%. The results of phylogenetic analysis, phenotypic analysis and chemotaxonomic studies showed that strain QX-2^T represents a novel species within the genus Halomonas, for which the name Halomonas sedimenti sp. nov. is proposed, with the type strain QX-2^T (MCCC 1A17876^T = KCTC 82199^T).

Evaluating the Bacterial Diversity from the Southwest Coast of India Using Fatty Acid Methyl Ester Profiles

The fatty acid composition of bacterial isolates remains stable under standardized culture conditions, which makes it a useful taxonomic marker. The present study aims to characterize the diversity and quantity of fatty acid methyl esters (FAME) profiles of cultivable bacterial isolates collected along the southwest coast of India. Based on the similarity indices (range > 0.3-0.7) of the FAME profiles, the isolates were aggregated into 10 families, 11 genera and 19 species of cultured isolates. The following classes of bacteria were found: Bacilli, Alphaproteobacteria, Betaproteobacteria, Gammaproteobacteria and Actinobacteria, which also included a few pathogens such as Pseudomonas, Staphylococcus and Bacillus sp. The hydroxyl FAMEs 2-hydroxydodecanoic acid (C_12:0 2OH), 2-hydroxypentadecanoic acid (C_15:0 2OH),3-hydroxy 14-methylpentadecanoic acid (C_16:0iso 3OH), 3 hydroxy hexadecenoic acid (C_16:0 3OH) and 3-hydroxy 15-methylhexadecanoic acid (C_17:0iso 3OH), as well as the unsaturated FAMEs (11Z)-11-hexadecenoic acid (C_16:1 ɷ5c), were exclusively associated with the isolates from Mangalore samples. Similarly, FAMEs 2-hydroxydecanoic acid (C_10:0 2OH), 9-methyldecanoic acid (C_11:0iso), undecanoic acid (C_11:0), tridecanoic acid (C_13:0), 10-methylhexadecanoic acid (C_16:0 10-CH₃) and (7Z)-7-hexadecenoic acid (C_16:1 ɷ9c) occurred only in the isolates from Trivandrum samples. However, the isolates from Goa did not possess a signature FAME profile. The reproducibility of the GC-MIDI bacterial identification system was evaluated using 16S rRNA gene sequencing techniques for selected isolates.

Combination of an Artificial Intelligence Approach and Laser Tweezers Raman Spectroscopy for Microbial Identification

Raman spectroscopy is a nondestructive, label-free, highly specific approach that provides the chemical information on materials. Thus, it is suitable to be used as an effective analytical tool to characterize biological samples. Here we introduce a novel method that uses artificial intelligence to analyze biological Raman spectra and identify the microbes at a single-cell level. The combination of a framework of convolutional neural network (ConvNet) and Raman spectroscopy allows the extraction of the Raman spectral features of a single microbial cell and then categorizes cells according to their spectral features. As the proof of concept, we measured Raman spectra of 14 microbial species at a single-cell level and constructed an optimal ConvNet model using the Raman data. The average accuracy of classification by ConvNet is 95.64 ± 5.46%. Meanwhile, we introduced an occlusion-based Raman spectra feature extraction to visualize the weights of Raman features for distinguishing different species.

Simulation of MICROBACT Strip Assay Using Colored Liquids to Demonstrate Identification of Unknown Gram-Negative Organisms in Undergraduate Laboratory

Identification of unknown microorganisms to the species level is an important component of a microbiology course. Modern technologies such as matrix assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) and 16S rRNA gene sequencing offer a rapid species level identification when compared to conventional phenotype-based methods, however they rely on a well-established taxonomy database and phenotypic assays can still play an important role in species determination. Another major limitation is the up-front cost of purchasing these modern specialized instruments and the requirement of skilled personnel to operate specialized equipment and software, which makes them unsuitable to use in the undergraduate teaching laboratory. Commercial biochemical identification systems such as the Oxoid Microbact™ GNB 12A/12E/24E kit is used for the identification of Enterobacteriaceae and other Gram negative bacteria in clinical and veterinary diagnostic laboratories, and food industries for disease control and treatment. In this article, we describe a method of reliably simulating this Microbact™ strip assay using artificial color liquids (which are affordable and easy to source) for the demonstration of phenotypic characterization of unknown Gram negative organisms while providing a safe teaching environment as no bacteria are used, familiarizing students with the concept of using Microbact™ 12A kit to identify a range of unknown Gram negative organisms.

Whole-Cell MALDI-TOF MS Versus 16S rRNA Gene Analysis for Identification and Dereplication of Recurrent Bacterial Isolates

Many ecological experiments are based on the extraction and downstream analyses of microorganisms from different environmental samples. Due to its high throughput, cost-effectiveness and rapid performance, Matrix Assisted Laser Desorption/Ionization Mass Spectrometry with Time-of-Flight detector (MALDI-TOF MS), which has been proposed as a promising tool for bacterial identification and classification, could be advantageously used for dereplication of recurrent bacterial isolates. In this study, we compared whole-cell MALDI-TOF MS-based analyses of 49 bacterial cultures to two well-established bacterial identification and classification methods based on nearly complete 16S rRNA gene sequence analyses: a phylotype-based approach, using a closest type strain assignment, and a sequence similarity-based approach involving a 98.65% sequence similarity threshold, which has been found to best delineate bacterial species. Culture classification using reference-based MALDI-TOF MS was comparable to that yielded by phylotype assignment up to the genus level. At the species level, agreement between 16S rRNA gene analysis and MALDI-TOF MS was found to be limited, potentially indicating that spectral reference databases need to be improved. We also evaluated the mass spectral similarity technique for species-level delineation which can be used independently of reference databases. We established optimal mass spectral similarity thresholds which group MALDI-TOF mass spectra of common environmental isolates analogically to phylotype- and sequence similarity-based approaches. When using a mass spectrum similarity approach, we recommend a mass range of 4-10 kDa for analysis, which is populated with stable mass signals and contains the majority of phylotype-determining peaks. We show that a cosine similarity (CS) threshold of 0.79 differentiate mass spectra analogously to 98.65% species-level delineation sequence similarity threshold, with corresponding precision and recall values of 0.70 and 0.73, respectively. When matched to species-level phylotype assignment, an optimal CS threshold of 0.92 was calculated, with associated precision and recall values of 0.83 and 0.64, respectively. Overall, our research indicates that a similarity-based MALDI-TOF MS approach can be routinely used for efficient dereplication of isolates for downstream analyses, with minimal loss of unique organisms. In addition, MALDI-TOF MS analysis has further improvement potential unlike 16S rRNA gene analysis, whose methodological limits have reached a plateau.