Droplet microfluidics has rapidly emerged as one of the key technologies opening up new experimental possibilities in microbiology. The ability to generate, manipulate and monitor droplets carrying single cells or small populations of bacteria in a highly parallel and high throughput manner creates new approaches for solving problems in diagnostics and for research on bacterial evolution. This review presents applications of droplet microfluidics in various fields of microbiology: i) detection and identification of pathogens, ii) antibiotic susceptibility testing, iii) studies of microbial physiology and iv) biotechnological selection and improvement of strains. We also list the challenges in the dynamically developing field and new potential uses of droplets in microbiology.

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Droplet microfluidics for microbiology: techniques, applications and challenges

Objectives: This study was aimed to assess the diversity of the meconium microbiome and determine if the bacterial community is affected by maternal diabetes status. Methods: The first intestinal discharge (meconium) was collected from 23 newborns stratified by maternal diabetes status: 4 mothers had pre-gestational type 2 diabetes mellitus (DM) including one mother with dizygotic twins, 5 developed gestational diabetes mellitus (GDM) and 13 had no diabetes. The meconium microbiome was profiled using multi-barcode 16S rRNA sequencing followed by taxonomic assignment and diversity analysis. Results: All meconium samples were not sterile and contained diversified microbiota. Compared with adult feces, the meconium showed a lower species diversity, higher sample-to-sample variation, and enrichment of Proteobacteria and reduction of Bacteroidetes. Among the meconium samples, the taxonomy analyses suggested that the overall bacterial content significantly differed by maternal diabetes status, with the microbiome of the DM group showing higher alphadiversity than that of no-diabetes or GDM groups. No global difference was found between babies delivered vaginally versus via Cesarean-section. Regression analysis showed that the most robust predictor for the meconium microbiota composition was the maternal diabetes status that preceded pregnancy. Specifically, Bacteroidetes (phyla) and Parabacteriodes (genus) were enriched in the meconium in the DM group compared to the no-diabetes group. Conclusions: Our study provides evidence that meconium contains diversified microbiota and is not affected by the mode of delivery. It also suggests that the meconium microbiome of infants born to mothers with DM is enriched for the same bacterial taxa as those reported in the fecal microbiome of adult DM patients.

https://academicworks.cuny.edu/cgi/viewcontent.cgi?article=1049&context=qc_pubs

Diversified Microbiota of Meconium Is Affected by Maternal Diabetes Status

Lignin is the most abundant aromatic substrate on Earth and its valorization technologies are still under developed. Depolymerization and fragmentation are the predominant preparatory strategies for valorization of lignin to chemicals and fuels. However, due to the structural heterogeneity of lignin, depolymerization and fragmentation typically result in diverse product species, which require extensive separation and purification procedures to obtain target products. For lignin valorization, bacterial-based systems have attracted increasing attention because of their diverse metabolisms, which can be used to funnel multiple lignin-based compounds into specific target products. Here, recent advances in lignin valorization using bacteria are critically reviewed, including lignin-degrading bacteria that are able to degrade lignin and use lignin-associated aromatics, various associated metabolic pathways, and application of bacterial cultures for lignin valorization. This review will provide insight into the recent breakthroughs and future trends of lignin valorization based on bacterial systems.

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Recent advances in lignin valorization with bacterial cultures: microorganisms, metabolic pathways, and bio-products

Bacteriophages from the Inoviridae family (inoviruses) are characterized by their unique morphology, genome content and infection cycle. One of the most striking features of inoviruses is their ability to establish a chronic infection whereby the viral genome resides within the cell in either an exclusively episomal state or integrated into the host chromosome and virions are continuously released without killing the host. To date, a relatively small number of inovirus isolates have been extensively studied, either for biotechnological applications, such as phage display, or because of their effect on the toxicity of known bacterial pathogens including Vibrio cholerae and Neisseria meningitidis. Here, we show that the current 56 members of the Inoviridae family represent a minute fraction of a highly diverse group of inoviruses. Using a machine learning approach leveraging a combination of marker gene and genome features, we identified 10,295 inovirus-like sequences from microbial genomes and metagenomes. Collectively, our results call for reclassification of the current Inoviridae family into a viral order including six distinct proposed families associated with nearly all bacterial phyla across virtually every ecosystem. Putative inoviruses were also detected in several archaeal genomes, suggesting that, collectively, members of this supergroup infect hosts across the domains Bacteria and Archaea. Finally, we identified an expansive diversity of inovirus-encoded toxin-antitoxin and gene expression modulation systems, alongside evidence of both synergistic (CRISPR evasion) and antagonistic (superinfection exclusion) interactions with co-infecting viruses, which we experimentally validated in a Pseudomonas model. Capturing this previously obscured component of the global virosphere may spark new avenues for microbial manipulation approaches and innovative biotechnological applications.

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Cryptic inoviruses revealed as pervasive in bacteria and archaea across Earth's biomes.

ABSTRACT Microbiologists have been using agar growth medium for over 120 years. It revolutionized microbiology in the 1890s when microbiologists were seeking effective methods to isolate microorganisms, which led to the successful cultivation of microorganisms as single clones. But there has been a disparity between total cell counts and cultivable cell counts on plates, often referred to as the “great plate count anomaly,” that has long been a phenomenon that still remains unsolved. Here, we report that a common practice microbiologists have employed to prepare agar medium has a hidden pitfall: when phosphate was autoclaved together with agar to prepare solid growth media (PT medium), total colony counts were remarkably lower than those grown on agar plates in which phosphate and agar were separately autoclaved and mixed right before solidification (PS medium). We used a pure culture of Gemmatimonas aurantiaca T-27T and three representative sources of environmental samples, soil, sediment, and water, as inocula and compared colony counts between PT and PS agar plates. There were higher numbers of CFU on PS medium than on PT medium using G. aurantiaca or any of the environmental samples. Chemical analysis of PT agar plates suggested that hydrogen peroxide was contributing to growth inhibition. Comparison of 454 pyrosequences of the environmental samples to the isolates revealed that taxa grown on PS medium were more reflective of the original community structure than those grown on PT medium. Moreover, more hitherto-uncultivated microbes grew on PS than on PT medium.

A Hidden Pitfall in the Preparation of Agar Media Undermines Microorganism Cultivability

Members of the gram-negative, strictly aerobic genus Comamonas occur in various environments. Here we report the complete genome of Comamonas testosteroni strain CNB-2. Strain CNB-2 has a circular chromosome that is 5,373,643 bp long and has a G+C content of 61.4%. A total of 4,803 open reading frames (ORFs) were identified; 3,514 of these ORFs are functionally assigned to energy production, cell growth, signal transduction, or transportation, while 866 ORFs encode hypothetical proteins and 423 ORFs encode purely hypothetical proteins. The CNB-2 genome has many genes for transportation (22%) and signal transduction (6%), which allows the cells to respond and adapt to changing environments. Strain CNB-2 does not assimilate carbohydrates due to the lack of genes encoding proteins involved in glycolysis and pentose phosphate pathways, and it contains many genes encoding proteins involved in degradation of aromatic compounds. We identified 66 Tct and nine TRAP-T systems and a complete tricarboxylic acid cycle, which may allow CNB-2 to take up and metabolize a range of carboxylic acids. This nutritional bias for carboxylic acids and aromatic compounds enables strain CNB-2 to occupy unique niches in environments. Four different sets of terminal oxidases for the respiratory system were identified, and they putatively functioned at different oxygen concentrations. This study conclusively revealed at the genomic level that the genetic versatility of C. testosteroni is vital for competition with other bacteria in its special niches.

http://www.im.ac.cn/UserFiles/File/2009/200912/AEM-75-6812t.pdf

The Complete Genome of Comamonas testosteroni Reveals Its Genetic Adaptations to Changing Environments

Deep learning plays a key role in the recent developments of machine learning. This paper develops a deep residual neural network (ResNet) for the regression of nonlinear functions. Convolutional layers and pooling layers are replaced by fully connected layers in the residual block. To evaluate the new regression model, we train and test neural networks with different depths and widths on simulated data, and we find the optimal parameters. We perform multiple numerical tests of the optimal regression model on multiple simulated data, and the results show that the new regression model behaves well on simulated data. Comparisons are also made between the optimal residual regression and other linear as well as nonlinear approximation techniques, such as lasso regression, decision tree, and support vector machine. The optimal residual regression model has better approximation capacity compared to the other models. Finally, the residual regression is applied into the prediction of a relative humidity series in the real world. Our study indicates that the residual regression model is stable and applicable in practice.

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Deep Residual Learning for Nonlinear Regression

We report a microfluidic device for automated sorting and cultivation of chemotactic microbes from pure cultures or mixtures. The device consists of two parts: in the first part, a concentration gradient of the chemoeffector was built across the channel for inducing chemotaxis of motile cells; in the second part, chemotactic cells from the sample were separated, and mixed with culture media to form nanoliter droplets for encapsulation, cultivation, enumeration, and recovery of single cells. Chemotactic responses were assessed by imaging and statistical analysis of droplets based on Poisson distribution. An automated procedure was developed for rapid enumeration of droplets with cell growth, following with scale-up cultivation on agar plates. The performance of the device was evaluated by the chemotaxis assays of Escherichia coli (E. coli) RP437 and E. coli RP1616. Moreover, enrichment and isolation of non-labelled Comamonas testosteroni CNB-1 from its 1:10 mixture with E. coli RP437 was demonstrated. The enrichment factor reached 36.7 for CNB-1, based on its distinctive chemotaxis toward 4-hydroxybenzoic acid. We believe that this device can be widely used in chemotaxis studies without necessarily relying on fluorescent labelling, and isolation of functional microbial species from various environments.

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Automated Chemotactic Sorting and Single-cell Cultivation of Microbes using Droplet Microfluidics.

Comamonas testosteroni strain CNB-1 was isolated from activated sludge and has been investigated for its ability to degrade 4-chloronitrobenzene. Results from this study showed that strain CNB-1 grew on phenol, gentisate, vanillate, 3-hydroxybenzoate (3HB), and 4-hydroxybenzoate (4HB) as carbon and energy sources. Proteomic data and enzyme activity assays suggested that vanillate, 3HB, and 4HB were degraded in strain CNB-1 via protocatechuate (PCA) 4,5-cleavage pathway. The genetics and biochemistry of the PCA 4,5-cleavage pathway were investigated. Results showed that the 4-oxalomesaconate (OMA) hydratase from C. testosteroni takes only enol-OMA as substrate. A previously functionally unknown gene pmdU encodes an OMA tautomerase and catalyzes conversion of OMAketo into OMAenol. The 4-carboxy-4-hydroxy-2-oxoadipate (CHA) aldolase is encoded by pmdF and catalyzes the last step of the PCA 4,5-cleavage pathway. We explored the 1,183 microbial genomes at GenBank for potential PCA 4,5-cleavage pathways, and 33 putative pmd clusters were found. Results suggest that PCA 4,5-cleavage pathways are mainly distributed in α- and β-Proteobacteria.

http://www.im.ac.cn/UserFiles/File/2012/2012-10/online.pdf

Assimilation of aromatic compounds by Comamonas testosteroni: characterization and spreadability of protocatechuate 4,5-cleavage pathway in bacteria

Microbes thrive and, in turn, influence the earth’s environment, but most are poorly understood because of our limited capacity to reveal their natural diversity and function. Developing novel tools and effective strategies are critical to ease this dilemma and will help to understand their roles in ecology and human health. Recently, droplet microfluidics is emerging as a promising technology for microbial studies with value in microbial cultivating, screening, and sequencing. This review aims to provide an overview of droplet microfluidics techniques for microbial research. First, some critical points or steps in the microfluidic system are introduced, such as droplet stabilization, manipulation, and detection. We then highlight the recent progress of droplet-based methods for microbiological applications, from high-throughput single-cell cultivation, screening to the targeted or whole-genome sequencing of single cells.

https://link.springer.com/content/pdf/10.1007/s42995-020-00082-8.pdf

Dongwei Chen

Papers

The Complete Genome of Comamonas testosteroni Reveals Its Genetic Adaptations to Changing Environments

Deep Residual Learning for Nonlinear Regression

Automated Chemotactic Sorting and Single-cell Cultivation of Microbes using Droplet Microfluidics.

Assimilation of aromatic compounds by Comamonas testosteroni: characterization and spreadability of protocatechuate 4,5-cleavage pathway in bacteria

One cell at a time: droplet-based microbial cultivation, screening and sequencing