Text-Mining to Identify Gene Sets Involved in Biocorrosion by Sulfate-Reducing Bacteria: A Semi-Automated Workflow

From genome to evolution: investigating type II methylotrophs using a pangenomic analysis

A comprehensive pangenomic approach was employed to analyze the genomes of 75 type II methylotrophs spanning various genera. Our investigation revealed 256 exact core gene families shared by all 75 organisms, emphasizing their crucial role in the survival and adaptability of these organisms. Additionally, we predicted the functionality of 12 hypothetical proteins. The analysis unveiled a diverse array of genes associated with key metabolic pathways, including methane, serine, glyoxylate, and ethylmalonyl-CoA (EMC) metabolic pathways. While all selected organisms possessed essential genes for the serine pathway, Methylooceanibacter marginalis lacked serine hydroxymethyltransferase (SHMT), and Methylobacterium variabile exhibited both isozymes of SHMT, suggesting its potential to utilize a broader range of carbon sources. Notably, Methylobrevis sp. displayed a unique serine-glyoxylate transaminase isozyme not found in other organisms. Only nine organisms featured anaplerotic enzymes (isocitrate lyase and malate synthase) for the glyoxylate pathway, with the rest following the EMC pathway. Methylovirgula sp. 4MZ18 stood out by acquiring genes from both glyoxylate and EMC pathways, and Methylocapsa sp. S129 featured an A-form malate synthase, unlike the G-form found in the remaining organisms. Our findings also revealed distinct phylogenetic relationships and clustering patterns among type II methylotrophs, leading to the proposal of a separate genus for Methylovirgula sp. 4M-Z18 and Methylocapsa sp. S129. This pangenomic study unveils remarkable metabolic diversity, unique gene characteristics, and distinct clustering patterns of type II methylotrophs, providing valuable insights for future carbon sequestration and biotechnological applications.

IMPORTANCE

Methylotrophs have played a significant role in methane-based product production for many years. However, a comprehensive investigation into the diverse genetic architectures across different genera of methylotrophs has been lacking. This study fills this knowledge gap by enhancing our understanding of core hypothetical proteins and unique enzymes involved in methane oxidation, serine, glyoxylate, and ethylmalonyl-CoA pathways. These findings provide a valuable reference for researchers working with other methylotrophic species. Furthermore, this study not only unveils distinctive gene characteristics and phylogenetic relationships but also suggests a reclassification for Methylovirgula sp. 4M-Z18 and Methylocapsa sp. S129 into separate genera due to their unique attributes within their respective genus. Leveraging the synergies among various methylotrophic organisms, the scientific community can potentially optimize metabolite production, increasing the yield of desired end products and overall productivity.

Optimization of sulfate reduction and methanogenesis via phase separation in a two-phase internal circulation reactor for the treatment of high-sulfate organic wastewater

To enhance the performance of the internal circulation (IC) reactor when treating high-sulfate organic wastewater, a laboratory-scale two-phase IC reactor with distinct phase separation capabilities was designed, and the sulfate reduction and methanogenesis processes were optimized by segregating the reactor into two specialized reaction zones. The results demonstrated that the first and second reaction areas of the two-phase IC reactor could be maintained at 4.5-6.0 and 7.5-8.5, respectively, turning them into the specialized phase for sulfate reduction and methanogenesis. Through phase separation, the two-phase IC reactor achieved a COD degradation and sulfate reduction efficiency of more than 80% when the influent sulfate concentration exceeded 5,000 mg/L, which were 32.32% and 16.04% higher than that before phase separation. Functional analyses indicated a greater activity of both the dissimilatory and assimilatory sulfate reduction pathways in the acidogenic phase, largely due to a rise in the relative abundance of the genera Desulfovibrio, Bacteroides, and Lacticaseibacillus, the primary carriers of sulfate reduction functional genes. In contrast, all the acetoclastic, hydrogenotrophic, and methylotrophic methanogenesis pathways were inhibited in the acidogenic phase but thrived in the methanogenic phase, coinciding with shifts in the genus Methanothrix, which harbors the mcrA, mcrB, and mcrG genes essential for the final transformation step of all three methanogenesis pathways.

U2-Net and ResNet50-Based Automatic Pipeline for Bacterial Colony Counting

In this paper, an automatic colony counting system based on an improved image preprocessing algorithm and convolutional neural network (CNN)-assisted automatic counting method was developed. Firstly, we assembled an LED backlighting illumination platform as an image capturing system to obtain photographs of laboratory cultures. Consequently, a dataset was introduced consisting of 390 photos of agar plate cultures, which included 8 microorganisms. Secondly, we implemented a new algorithm for image preprocessing based on light intensity correction, which facilitated clearer differentiation between colony and media areas. Thirdly, a U2-Net was used to predict the probability distribution of the edge of the Petri dish in images to locate region of interest (ROI), and then threshold segmentation was applied to separate it. This U2-Net achieved an F1 score of 99.5% and a mean absolute error (MAE) of 0.0033 on the validation set. Then, another U2-Net was used to separate the colony region within the ROI. This U2-Net achieved an F1 score of 96.5% and an MAE of 0.005 on the validation set. After that, the colony area was segmented into multiple components containing single or adhesive colonies. Finally, the colony components (CC) were innovatively rotated and the image crops were resized as the input (with 14,921 image crops in the training set and 4281 image crops in the validation set) for the ResNet50 network to automatically count the number of colonies. Our method achieved an overall recovery of 97.82% for colony counting and exhibited excellent performance in adhesion classification. To the best of our knowledge, the proposed "light intensity correction-based image preprocessing→U2-Net segmentation for Petri dish edge→U2-Net segmentation for colony region→ResNet50-based counting" scheme represents a new attempt and demonstrates a high degree of automation and accuracy in recognizing and counting single-colony and multi-colony targets.

Convergence research and training in computational bioengineering: a case study on AI/ML driven biofilm-material interaction discovery

Initially, research disciplines operated independently, but the emergence of trans-disciplinary sciences led to convergence research, impacting graduate programs and research laboratories, especially in bioengineering and material engineering as presented here. Current graduate curriculum fails to efficiently prepare students for multidisciplinary and convergence research, thus creating a gap between the students and research laboratory expectations. We present a convergence training framework for graduate students, incorporating problem-based learning under the guidance of senior scientists and collaboration with postdoctoral researchers. This case study serves as a template for transdisciplinary convergent training projects - bridging the expertise gap and fostering successful convergence learning experiences in computational biointerface (material-biology interface). The 18-month Advanced Data Science Workshop, initiated in 2019, involves project-based learning, online training modules, and data collection. A pilot solution utilized Jupyter notebook on Google collaborator and culminated in a face-to-face workshop where project presentations and finalization occurred. The program started with 9 experts in the four diverse fields creating 14 curated projects in data science (Artificial Intelligence/Machine Learning), material science, biofilm engineering, and biointerface. These were integrated into convergence research through webinars by the experts. The experts chose 8 of the 14 projects to be part of an all-day in-person workshop, where over 20 learners formed eight teams that tackled complex problems at the interface of digital image processing, gene expression analysis, and material prediction. Each team was comprised of students and postdoctoral researchers or research scientists from diverse domains including computer science, materials science, and biofilm research. Some projects were selected for presentation at the international IEEE Bioinformatics conference in 2022, with three resulting Machine Learning (ML) models submitted as a journal paper. Students engaged in problem discussions, collaborated with experts from different disciplines, and received guidance in decomposing learning objectives. Based on learner feedback, this successful experience allows for consolidation and integration of convergence research via problem-based learning into the curriculum. Three bioengineering participants, who received training in data science and engineering, have received bioinformatics jobs in biotechnology industries.

The Isolation of Anaerobic and Facultative Anaerobic Sulfate-Reducing Bacteria (SRB) and a Comparison of Related Enzymes in Their Sulfate Reduction Pathways

Sulfate-reducing bacteria (SRB) are an important group of microorganisms that cause microbial corrosion. In this study, culturable SRB were isolated and identified from the inner rust layer of three kinds of steel and from sediments, and a comparison of amino acid sequences encoding related enzymes in the sulfate reduction pathway between anaerobic and facultative anaerobic SRB strains was carried out. The main results are as follows. (1) Seventy-seven strains were isolated, belonging to five genera and seven species, with the majority being Desulfovibrio marinisediminis. For the first time, Holodesulfovibrio spirochaetisodalis and Acinetobacter bereziniae were separated from the inner rust layer of metal, and sulfate reduction by A. bereziniae, Virgibacillus dokdonensis, and Virgibacillus chiguensis, etc., was also demonstrated for the first time. (2) Three strains of strictly anaerobic bacteria and four strains of facultative anaerobic bacteria were screened from seven bacterial strains. (3) Most of the anaerobic SRB only contained enzymes for the dissimilatory sulfate reduction pathway, while those of facultative anaerobic bacteria capable of producing hydrogen sulfide included two possible ways: containing the related enzymes from the dissimilatory pathway only, or containing enzymes from both dissimilatory and assimilation pathways. This study newly discovered that some bacterial genera exhibit sulfate reduction ability and found that there are differences in the distribution of enzymes related to the sulfate reduction pathway between anaerobic and facultative anaerobic SRB type trains, providing a basis for the development and utilization of sulfate-reducing bacterial resources and furthering our understanding of the metabolic mechanisms of SRB.