Genetic evidence for functional diversification of gram-negative intermembrane phospholipid transporters.

The outer membrane of gram-negative bacteria is a barrier to chemical and physical stress. Phospholipid transport between the inner and outer membranes has been an area of intense investigation and, in E. coli K-12, it has recently been shown to be mediated by YhdP, TamB, and YdbH, which are suggested to provide hydrophobic channels for phospholipid diffusion, with YhdP and TamB playing the major roles. However, YhdP and TamB have different phenotypes suggesting distinct functions. It remains unclear whether these functions are related to phospholipid metabolism. We investigated a synthetic cold sensitivity caused by deletion of fadR, a transcriptional regulator controlling fatty acid degradation and unsaturated fatty acid production, and yhdP, but not by ΔtamB ΔfadR or ΔydbH ΔfadR. Deletion of tamB recuses the ΔyhdP ΔfadR cold sensitivity further demonstrating the phenotype is related to functional diversification between these genes. The ΔyhdP ΔfadR strain shows a greater increase in cardiolipin upon transfer to the non-permissive temperature and genetically lowering cardiolipin levels can suppress cold sensitivity. These data also reveal a qualitative difference between cardiolipin synthases in E. coli, as deletion of clsA and clsC suppresses cold sensitivity but deletion of clsB does not. Moreover, increased fatty acid saturation is necessary for cold sensitivity and lowering this level genetically or through supplementation of oleic acid suppresses the cold sensitivity of the ΔyhdP ΔfadR strain. Together, our data clearly demonstrate that the diversification of function between YhdP and TamB is related to phospholipid metabolism. Although indirect regulatory effects are possible, we favor the parsimonious hypothesis that YhdP and TamB have differential phospholipid-substrate transport preferences. Thus, our data provide a potential mechanism for independent control of the phospholipid composition of the inner and outer membranes in response to changing conditions based on regulation of abundance or activity of YhdP and TamB.

Spatial proximity and gene function: a new dimension in prokaryotic gene association network analysis with 3D-GeneNet.

Understanding the biological functions and processes of genes, particularly those not yet characterized, is crucial for advancing molecular biology and identifying therapeutic targets. The hypothesis guiding this study is that the 3D proximity of genes correlates with their functional interactions and relevance in prokaryotes. We introduced 3D-GeneNet, an innovative software tool that utilizes high-throughput sequencing data from chromosome conformation capture techniques and integrates topological metrics to construct gene association networks. Through a series of comparative analyses focused on spatial versus linear distances, we explored various dimensions such as topological structure, functional enrichment levels, distribution patterns of linear distances among gene pairs, and the area under the receiver operating characteristic curve by utilizing model organism Escherichia coli K-12. Furthermore, 3D-GeneNet was shown to maintain good accuracy compared to multiple algorithms (neighbourhood, co-occurrence, coexpression, and fusion) across multiple bacteria, including E. coli, Brucella abortus, and Vibrio cholerae. In addition, the accuracy of 3D-GeneNet's prediction of long-distance gene interactions was identified by bacterial two-hybrid assays on E. coli K-12 MG1655, where 3D-GeneNet not only increased the accuracy of linear genomic distance tripled but also achieved 60% accuracy by running alone. Finally, it can be concluded that the applicability of 3D-GeneNet will extend to various bacterial forms, including Gram-negative, Gram-positive, single-, and multi-chromosomal bacteria through Hi-C sequencing and analysis. Such findings highlight the broad applicability and significant promise of this method in the realm of gene association network. 3D-GeneNet is freely accessible at https://github.com/gaoyuanccc/3D-GeneNet.

Elucidation of the Gemcitabine Transporters of Escherichia coli K-12 and Gamma-Proteobacteria Linked to Gemcitabine-Related Chemoresistance.

Gemcitabine (2',2'-difluoro-2'-deoxycytidine), a widely used anticancer drug, is considered a gold standard in treating aggressive pancreatic cancers. Gamma-proteobacteria that colonize the pancreatic tumors contribute to chemoresistance against gemcitabine by metabolizing the drug to a less active and deaminated form. The gemcitabine transporters of these bacteria are unknown to date. Furthermore, there is no complete knowledge of the gemcitabine transporters in Escherichia coli or any other related proteobacteria. In this study, we investigate the complement of gemcitabine transporters in E. coli K-12 and two common chemoresistance-related bacteria (Klebsiella pneumoniae and Citrobacter freundii). We found that E. coli K-12 has two high-affinity gemcitabine transporters with distinct specificity properties, namely, NupC and NupG, whereas the gemcitabine transporters of C. freundii and K. pneumoniae include the NupC and NupG orthologs, functionally indistinguishable from their counterparts, and, in K. pneumoniae, one additional NupC variant, designated KpNupC2. All these bacterial transporters have a higher affinity for gemcitabine than their human counterparts. The highest affinity (KM 2.5-3.0 µΜ) is exhibited by NupGs of the bacteria-specific nucleoside-H+ symporter (NHS) family followed by NupCs (KM 10-13 µΜ) of the concentrative nucleoside transporter (CNT) family, 15-100 times higher than the affinities reported for the human gemcitabine transporter hENT1/SLC29A1, which is primarily associated with gemcitabine uptake in the pancreatic adenocarcinoma cells. Our results offer a basis for further insight into the role of specific bacteria in drug availability within tumors and for understanding the structure-function differences of bacterial and human drug transporters.

Unlocking the potential of Escherichia coli K-12: A novel approach for malignancy reduction in colorectal cancer through gene expression modulation.

Studies have noted the association between Escherichia coli K-12 (E. coli K-12) and the reduction of malignancy in colorectal cancer (CRC). However, the molecular mechanisms underlying this relationship have not been thoroughly explored. The aim of this study was to identify the genes influenced by E. coli K-12 and their connection to CRC. We identified the genes affected by E. coli K-12 using the GSE50040 dataset. Additionally, we investigated the relationship between the expression of genes affected by E. coli K-12 and CRC using the cancer genome atlas data. The association between the expression of E. coli K-12-affected genes and patient prognosis was investigated using clinical data. Pathways related to CRC and E. coli K-12-related genes were analyzed using the Enrichr tool. Furthermore, we employed a protein-protein interaction (PPI) network to identify hub genes associated with both E. coli K-12 and CRC. To validate our findings, we conducted RT-qPCR analysis on CRC samples and adjacent normal tissue. The results of GSE50040 showed that E. coli K-12 could change the expression of many genes related to CRC in colorectal cell lines. The results showed that E. coli K-12 reduces the expression of several genes linked to the main pathways used by cancer cells, such as the metastasis, WNT, cell proliferation pathway, and mTORC1. It was demonstrated that elevated BGN, FJX1, and LZTS1 expression is linked to a bad prognosis in patients and that E. coli K-12 may be able to lower this expression. Also, based on the PPI network, genes such as KLF4 and CXCL3 were identified as hub genes related to genes affected by E. coli K-12. When KLF4 and CXCL3 expression levels in cancer samples were compared to nearby normal tissue, a significant change in these genes' expression levels was found in CRC. Our findings demonstrated the potential relationship between oncogene genes and genes impacted by E. coli K-12. Also, our findings demonstrated that E. coli K-12 may regulate the expression of genes linked to a high death rate. In summary, the results of this study suggest that E. coli K-12 can be regarded as a significant probiotic with the potential to mitigate the risk of CRC development.

Genomic SELEX Screening of Regulatory Targets of Transcription Factors.

The genome of Escherichia coli K-12 is transcribed by a single species of RNA polymerase. The selectivity of transcriptional targets is determined via interaction with one of seven species of the sigma subunit and a total of approximately 300 species of transcription factor (TFs). For comprehensive identification of the regulatory targets of these two groups of regulatory proteins on the genome, we developed an in vitro approach, "Genomic SELEX" (gSELEX) screening. Here we describe a detailed protocol of the gSELEX screening system, which uses purified regulatory proteins and fragments of genomic DNA from E. coli. Moreover, we describe methods and examples of results using cell-free synthetic proteins.

Discovery of a Gut Bacterial Metabolic Pathway that Drives α-Synuclein Aggregation.

Parkinson's disease (PD) etiology is associated with aggregation and accumulation of α-synuclein (α-syn) proteins in midbrain dopaminergic neurons. Emerging evidence suggests that in certain subtypes of PD, α-syn aggregates originate in the gut and subsequently spread to the brain. However, mechanisms that instigate α-syn aggregation in the gut have remained elusive. In the brain, the aggregation of α-syn is induced by oxidized dopamine. Such a mechanism has not been explored in the context of the gastrointestinal tract, a niche harboring 46% of the body's dopamine reservoirs. Here, we report that Enterobacteriaceae, a bacterial family prevalent in human gut microbiotas, induce α-syn aggregation. More specifically, our in vitro data indicate that respiration of nitrate by Escherichia coli K-12, which results in production of nitrite that mediates oxidation of Fe2+ to Fe3+, creates an oxidizing redox potential. These oxidizing conditions enabled the formation of dopamine-derived quinones and α-syn aggregates. Exposing nitrite, but not nitrate, to enteroendocrine STC-1 cells induced aggregation of α-syn that is natively expressed in these cells, which line the intestinal tract. Taken together, our findings indicate that bacterial nitrate reduction may be critical for initiating intestinal α-syn aggregation.

Integrative in vivo analysis of the ethanolamine utilization bacterial microcompartment in Escherichia coli.

Bacterial microcompartments (BMCs) are self-assembling protein megacomplexes that encapsulate metabolic pathways. Although approximately 20% of sequenced bacterial genomes contain operons encoding putative BMCs, few have been thoroughly characterized, nor any in the most studied Escherichia coli strains. We used an interdisciplinary approach to gain deep molecular and functional insights into the ethanolamine utilization (Eut) BMC system encoded by the eut operon in E. coli K-12. The eut genotype was linked with the ethanolamine utilization phenotype using deletion and overexpression mutants. The subcellular dynamics and morphology of the E. coli Eut BMCs were characterized in cellula by fluorescence microscopy and electron (cryo)microscopy. The minimal proteome reorganization required for ethanolamine utilization and the in vivo stoichiometric composition of the Eut BMC were determined by quantitative proteomics. Finally, the first flux map connecting the Eut BMC with central metabolism in cellula was obtained by genome-scale modeling and 13C-fluxomics. Our results reveal that contrary to previous suggestions, ethanolamine serves both as a nitrogen and a carbon source in E. coli K-12, while also contributing to significant metabolic overflow. Overall, this study provides a quantitative molecular and functional understanding of the BMCs involved in ethanolamine assimilation by E. coli.IMPORTANCEThe properties of bacterial microcompartments make them an ideal tool for building orthogonal network structures with minimal interactions with native metabolic and regulatory networks. However, this requires an understanding of how BMCs work natively. In this study, we combined genetic manipulation, multi-omics, modeling, and microscopy to address this issue for Eut BMCs. We show that the Eut BMC in Escherichia coli turns ethanolamine into usable carbon and nitrogen substrates to sustain growth. These results improve our understanding of compartmentalization in a widely used bacterial chassis.

Analyzing the correlation between protein expression and sequence-related features of mRNA and protein in Escherichia coli K-12 MG1655 model.

It was necessary to have a tool that could predict the amount of protein and optimize the gene sequences to produce recombinant proteins efficiently. The Transim model published by Tuller et al. in 2018 can calculate the translation rate in E. coli using features on the mRNA sequence, achieving a Spearman correlation with the amount of protein per mRNA of 0.36 when tested on the dataset of operons' first genes in E. coli K-12 MG1655 genome. However, this Spearman correlation was not high, and the model did not fully consider the features of mRNA and protein sequences. Therefore, to enhance the prediction capability, our study firstly tried expanding the testing dataset, adding genes inside the operon, and using the microarray of the mRNA expression data set, thereby helping to improve the correlation of translation rate with the amount of protein with more than 0.42. Next, the applicability of 6 traditional machine learning models to calculate a "new translation rate" was examined using initiation rate and elongation rate as inputs. The result showed that the SVR algorithm had the most correlated new translation rates, with Spearman correlation improving to R = 0.6699 with protein level output and to R = 0.6536 with protein level per mRNA. Finally, the study investigated the degree of improvement when combining more features with the new translation rates. The results showed that the model's predictive ability to produce a protein per mRNA reached R = 0.6660 when using six features, while the correlation of this model's final translation rate to protein level was up to R = 0.6729. This demonstrated the model's capability to predict protein expression of a gene, rather than being limited to predicting expression by an mRNA and showed the model's potential for development into gene expression predicting tools.

Bactericidal effect of tetracycline in E. coli strain ED1a may be associated with ribosome dysfunction.

Ribosomes translate the genetic code into proteins. Recent technical advances have facilitated in situ structural analyses of ribosome functional states inside eukaryotic cells and the minimal bacterium Mycoplasma. However, such analyses of Gram-negative bacteria are lacking, despite their ribosomes being major antimicrobial drug targets. Here we compare two E. coli strains, a lab E. coli K-12 and human gut isolate E. coli ED1a, for which tetracycline exhibits bacteriostatic and bactericidal action, respectively. Using our approach for close-to-native E. coli sample preparation, we assess the two strains by cryo-ET and visualize their ribosomes at high resolution in situ. Upon tetracycline treatment, these exhibit virtually identical drug binding sites, yet the conformation distribution of ribosomal complexes differs. While K-12 retains ribosomes in a translation-competent state, tRNAs are lost in the vast majority of ED1a ribosomes. These structural findings together with the proteome-wide abundance and thermal stability assessments indicate that antibiotic responses are complex in cells and can differ between different strains of a single species, thus arguing that all relevant bacterial strains should be analyzed in situ when addressing antibiotic mode of action.