A novel sulfonamide resistance mechanism by two-component flavin-dependent monooxygenase system in sulfonamide-degrading actinobacteria

Sulfonamide-degrading bacteria have been discovered in various environments, suggesting the presence of novel resistance mechanisms via drug inactivation. In this study, Microbacterium sp. CJ77 capable of utilizing various sulfonamides as a sole carbon source was isolated from a composting facility. Genome and proteome analyses revealed that a gene cluster containing a flavin-dependent monooxygenase and a flavin reductase was highly up-regulated in response to sulfonamides. Biochemical analysis showed that the two-component monooxygenase system was key enzymes for the initial cleavage of sulfonamides. Co-expression of the two-component system in Escherichia coli conferred decreased susceptibility to sulfamethoxazole, indicating that the genes encoding drug-inactivating enzymes are potential resistance determinants. Comparative genomic analysis revealed that the gene cluster containing sulfonamide monooxygenase (renamed as sulX) and flavin reductase (sulR) was highly conserved in a genomic island shared among sulfonamide-degrading actinobacteria, all of which also contained sul1-carrying class 1 integrons. These results suggest that the sulfonamide metabolism may have evolved in sulfonamide-resistant bacteria which had already acquired the class 1 integron under sulfonamide selection pressures. Furthermore, the presence of multiple insertion sequence elements and putative composite transposon structures containing the sulX gene cluster indicated potential mobilization. This is the first study to report that sulX responsible for both sulfonamide degradation and resistance is prevalent in sulfonamide-degrading actinobacteria and its genetic signatures indicate horizontal gene transfer of the novel resistance gene

Mobile resistome of human gut and pathogen drives anthropogenic bloom of antibiotic resistance

BACKGROUND:The impact of human activities on the environmental resistome has been documented in many studies, but there remains the controversial question of whether the increased antibiotic resistance observed in anthropogenically impacted environments is just a result of contamination by resistant fecal microbes or is mediated by indigenous environmental organisms. Here, to determine exactly how anthropogenic influences shape the environmental resistome, we resolved the microbiome, resistome, and mobilome of the planktonic microbial communities along a single river, the Han, which spans a gradient of human activities. RESULTS:The bloom of antibiotic resistance genes (ARGs) was evident in the downstream regions and distinct successional dynamics of the river resistome occurred across the spatial continuum. We identified a number of widespread ARG sequences shared between the river, human gut, and pathogenic bacteria. These human-related ARGs were largely associated with mobile genetic elements rather than particular gut taxa and mainly responsible for anthropogenically driven bloom of the downstream river resistome. Furthermore, both sequence- and phenotype-based analyses revealed environmental relatives of clinically important proteobacteria as major carriers of these ARGs. CONCLUSIONS:Our results demonstrate a more nuanced view of the impact of anthropogenic activities on the river resistome: fecal contamination is present and allows the transmission of ARGs to the environmental resistome, but these mobile genes rather than resistant fecal bacteria proliferate in environmental relatives of their original hosts. Video abstract

“Four Joints of Power” Innovation of Community Involvement in Medical Waste Management of Bed-Bound Patients in Thailand

This study aims to encourage innovative participation in the management of medical waste by bedridden patients in the research region of Khon Sawan, Chaiaphum Province, through research and development. The steps were as follows: Phase 1: Study of bedridden patient waste management situations using the amount of waste generated through innovation with relatives, non-relatives, village health volunteers (VHVs), and community leaders. Phase 2: Developing creative waste management engagement requires two steps: (1) analyzing the problem or its cause and generating management alternatives through collaborative brainstorming with a community member and (2) gathering the thoughts and suggestions of a number of agency specialists. The outcome is a novel model of participation in waste management by bedridden patients termed “Four Joins of Power,” which includes (1) participatory activities and enhancing community knowledge and attitudes, and (2) providing information on the management of each type of waste. (3) cooperation in waste management (analytical thinking, planning, execution, etc.) and regulation by mutually agreed-upon rules. (4) joint expansion of the waste management network: Phase 3 is the innovation trial, and Phase 4 is the innovation assessment. The paired t-test was used to compare pre-and post-development knowledge and attitudes, and to conduct qualitative data analysis. In Phase 3, after implementing collaborative innovations, the average knowledge (X¯ = 13.23) and attitudes (X¯ = 4.14) regarding waste management increased considerably (p X¯ = 4.25 and X¯ = 4.27). Among the most collaborative participants, 93.50% were satisfied. To reduce the amount of waste that must be sorted and collected, it is necessary to emphasize the participation of people and networks from all sectors in the area through joint thinking, planning, and comprehensive analysis, to ensure the sustainability of waste management in the community

Transcriptome software results show significant variation among different commercial pipelines

Abstract Background We have been documenting the biological responses to low levels of radiation (natural background) and very low level radiation (below background), and thus these studies are testing mild external stimuli to which we would expect relatively mild biological responses. We recently published a transcriptome software comparison study based on RNA-Seqs from a below background radiation treatment of two model organisms, E. coli and C. elegans (Thawng and Smith, BMC Genomics 23:452, 2022). We reported DNAstar-D (Deseq2 in the DNAstar software pipeline) to be the more conservative, realistic tool for differential gene expression compared to other transcriptome software packages (CLC, Partek and DNAstar-E (using edgeR). Here we report two follow-up studies (one with a new model organism, Aedes aegypti and another software package (Azenta) on transcriptome responses from varying dose rates using three different sources of natural radiation. Results When E. coli was exposed to varying levels of K40, we again found that the DNAstar-D pipeline yielded a more conservative number of DEGs and a lower fold-difference than the CLC pipeline and DNAstar-E run in parallel. After a 30 read minimum cutoff criterion was applied to the data, the number of significant DEGs ranged from 0 to 81 with DNAstar-D, while the number of significant DEGs ranged from 4 to 117 and 14 to 139 using DNAstar-E and the CLC pipelines, respectively. In terms of the extent of expression, the highest foldchange DEG was observed in DNAstar-E with 19.7-fold followed by 12.5-fold in CLC and 4.3-fold in DNAstar-D. In a recently completed study with Ae. Aegypti and using another software package (Azenta), we analyzed the RNA-Seq response to similar sources of low-level radiation and again found the DNAstar-D pipeline to give the more conservative number and fold-expression of DEGs compared to other softwares. The number of significant DEGs ranged 31–221 in Azenta and 31 to 237 in CLC, 19–252 in DNAstar-E and 0–67 in DNAStar-D. The highest fold-change of DEGs were found in CLC (1,350.9-fold), with DNAstar-E (5.9 -fold) and Azenta (5.5-fold) intermediate, and the lowest levels of expression (4-fold) found in DNAstar-D. Conclusions This study once again highlights the importance of choosing appropriate software for transcriptome analysis. Using three different biological models (bacteria, nematode and mosquito) in four different studies testing very low levels of radiation (Van Voorhies et al., Front Public Health 8:581796, 2020; Thawng and Smith, BMC Genomics 23:452, 2022; current study), the CLC software package resulted in what appears to be an exaggerated gene expression response in terms of numbers of DEGs and extent of expression. Setting a 30-read cutoff diminishes this exaggerated response in most of the software tested. We have further affirmed that DNAstar-Deseq2 gives a more conservative transcriptome expression pattern which appears more suitable for studies expecting subtle gene expression patterns