Genomic insights into the antibiotic resistance pattern of the tetracycline-degrading bacterium, Arthrobacter nicotianae OTC-16

Effects of sulfamethazine and tetracycline at molecular, cellular and tissue levels in Eisenia fetida earthworms

Soil contamination by antibiotics is a global issue of great concern that contributes to the rise of bacterial antibiotic resistance and can have toxic effects on non-target organisms. This study evaluated the variations of molecular, cellular, and histological parameters in Eisenia fetida earthworms exposed to sulfamethazine (SMZ) and tetracycline (TC), two antibiotics commonly found in agricultural soils. The earthworms were exposed for 14 days to a series of concentrations (0, 10, 100, and 1000 mg/kg) of both antibiotics. SMZ and TC did not affect the survival of E. fetida, however, other effects at different levels of biological complexity were detected. The two highest concentrations of SMZ reduced the viability of coelomocytes. At the highest TC concentration, there was a noticeable decline in cell viability, acetylcholinesterase activity (neurotoxicity), and the relative presence of mucopolysaccharides in the epidermis (mucous production). Glutathione S-transferase activity decreased in all TC treatments and at the highest SMZ concentration. However, levels of malondialdehyde and protein carbonyls did not change, suggesting an absence of oxidative stress. Tetracycline was neurotoxic to E. fetida and changed the integrity of the epidermis. Both antibiotics altered the intestinal microbiota of E. fetida, leading to a reduction in the relative abundance of bacteria from the phyla Proteobacteria and Bacteroidetes, while causing an increase in the phylum Actinobacteroidota. All observed changes indicate that both SMZ and TC can disrupt the earthworms' immune system and gut microbiome, while fostering the growth of bacteria that harbour antibiotic resistance genes. Finally, both antibiotics exerted additional metabolic and physiological effects that increased the vulnerability of E. fetida to pathogens.

Sulfadiazine degradation by Bjerkandera adusta DH0817 at low temperatures and its cold-adaptation mechanisms

The prolonged period of low temperatures in northern China poses a significant challenge to the bioremediation of antibiotic pollution. This study reports that a white-rot fungus Bjerkandera adusta DH0817, isolated from a poultry farm in Liaoning Province, can remove 60 % of SDZ within 20 days at 10°C and reduce the biotoxicity of SDZ. Six degradation pathways were proposed. SDZ biodegradation was primarily driven by cytochrome P450. Transcriptome analysis revealed that DH0817 upregulated genes associated with cell membrane, transcription factors and soluble sugars in response to low temperatures. Subsequently, genes associated with fatty acid, proteins and enzymes were upregulated to remove SDZ at low temperatures. This study provides valuable microbial resources and serves as a theoretical reference for addressing antibiotic pollution in livestock and poultry farms under low temperature conditions.

Whole Genome Sequencing: Applications in Clinical Bacteriology

The success in determining the whole genome sequence of a bacterial pathogen was first achieved in 1995 by determining the complete nucleotide sequence of Haemophilus influenzae Rd using the chain-termination method established by Sanger et al. in 1977 and automated by Hood et al. in 1987. However, this technology was laborious, costly, and time-consuming. Since 2004, high-throughput next-generation sequencing technologies have been developed, which are highly efficient, require less time, and are cost-effective for whole genome sequencing (WGS) of all organisms, including bacterial pathogens. In recent years, the data obtained using WGS technologies coupled with bioinformatics analyses of the sequenced genomes have been projected to revolutionize clinical bacteriology. WGS technologies have been used in the identification of bacterial species, strains, and genotypes from cultured organisms and directly from clinical specimens. WGS has also helped in determining resistance to antibiotics by the detection of antimicrobial resistance genes and point mutations. Furthermore, WGS data have helped in the epidemiological tracking and surveillance of pathogenic bacteria in healthcare settings as well as in communities. This review focuses on the applications of WGS in clinical bacteriology.

Metagenomic binning analyses of pig manure composting reveal potential antibiotic-degrading bacteria and their risk of antibiotic resistance genes

Antibiotic-degrading bacteria are commonly used to treat antibiotic contamination, but the antibiotic resistance genes (ARGs) they carry are often overlooked. This study used metagenomic assembly and binning analyses to explore potential antibiotic-degrading bacteria and their ARGs during pig manure composting. The result showed that 35 metagenome-assembled genomes (MAGs) mainly containing alkyl-aryl transferase and decarboxylase genes involved in the removal of antibiotics. Multidrug (124), β-lactam (67), macrolide-lincosamide-streptogramin (MLS) (64), and tetracycline (43) were the central ARG types detected in the 35 MAGs. Furthermore, the risk of ARGs was evaluated using the arg_ranker framework, and 19 MAGs were found to contain intermediate-high-risk ARGs with human-associated-enrichment, gene transferability, and host pathogenicity. Bin 34 of the genus of Geofilum had the highest ARG risk. Bin 6, Bin 11 and Bin 14 of the genus of Limnochorda, Chelatococcus and Niabella, had a lower ARG risk and were considered as potential antibiotic-degrading bacteria.

Systems Biology: New Insight into Antibiotic Resistance

Over the past few decades, antimicrobial resistance (AMR) has emerged as an important threat to public health, resulting from the global propagation of multidrug-resistant strains of various bacterial species. Knowledge of the intrinsic factors leading to this resistance is necessary to overcome these new strains. This has contributed to the increased use of omics technologies and their extrapolation to the system level. Understanding the mechanisms involved in antimicrobial resistance acquired by microorganisms at the system level is essential to obtain answers and explore options to combat this resistance. Therefore, the use of robust whole-genome sequencing approaches and other omics techniques such as transcriptomics, proteomics, and metabolomics provide fundamental insights into the physiology of antimicrobial resistance. To improve the efficiency of data obtained through omics approaches, and thus gain a predictive understanding of bacterial responses to antibiotics, the integration of mathematical models with genome-scale metabolic models (GEMs) is essential. In this context, here we outline recent efforts that have demonstrated that the use of omics technology and systems biology, as quantitative and robust hypothesis-generating frameworks, can improve the understanding of antibiotic resistance, and it is hoped that this emerging field can provide support for these new efforts.

Chryseobacterium subflavum sp. nov., isolated from soil

A Gram-stain-negative, aerobic, non-motile, rod-shaped bacterium, designated LAMRS1T, was isolated from a soil sample collected in Hebei Province, PR China. Strain LAMRS1T was able to grow optimally in the presence of 0.5 % (w/v) NaCl, at pH 7.5 and at 30 °C. On the basis of 16S rRNA gene sequence analysis, strain LAMRS1T was closely related to members of the genus Chryseobacterium , with highest levels of sequence similarity to Chryseobacterium soli DSM 19298T (97.9 %), Chryseobacterium soldanellicola DSM 17072T (97.6%) and Chryseobacterium piperi CTMT (97.5 %). The average nucleotide identity and digital DNA–DNA hybridization values between LAMRS1T and the closely related species of C. soli DSM 19298T, C. soldanellicola DSM 17072T and C. piperi CTMT were 78.1, 78.2 and 80.7 %, and 21.7, 22.0 and 23.7 %, respectively. The draft genome sequence of LAMRS1T was 4.61 Mb, with DNA G+C content of 36.2 mol%. The major isoprenoid quinone was menaquinone-6 and iso-C15 : 0, iso-C17 : 0 3-OH and summed feature 3 (C16 : 1  ω6c and/or C16 : 1  ω7c) constituted the major cellular fatty acids. The main polar lipids were phosphatidylethanolamine, four aminolipids, three glycolipids and seven unidentified lipids. On the basis of evidence presented in this study, strain LAMRS1T represents a novel species of the genus Chryseobacterium , for which the name Chryseobacterium subflavum sp. nov. is proposed. The type strain is LAMRS1T (=JCM 33868T=KCTC 72823T).

An Overview of Antibiotic Resistance and Abiotic Stresses Affecting Antimicrobial Resistance in Agricultural Soils

Excessive use of antibiotics in the healthcare sector and livestock farming has amplified antimicrobial resistance (AMR) as a major environmental threat in recent years. Abiotic stresses, including soil salinity and water pollutants, can affect AMR in soils, which in turn reduces the yield and quality of agricultural products. The objective of this study was to investigate the effects of antibiotic resistance and abiotic stresses on antimicrobial resistance in agricultural soils. A systematic review of the peer-reviewed published literature showed that soil contaminants derived from organic and chemical fertilizers, heavy metals, hydrocarbons, and untreated sewage sludge can significantly develop AMR through increasing the abundance of antibiotic resistance genes (ARGs) and antibiotic-resistant bacteria (ARBs) in agricultural soils. Among effective technologies developed to minimize AMR's negative effects, salinity and heat were found to be more influential in lowering ARGs and subsequently AMR. Several strategies to mitigate AMR in agricultural soils and future directions for research on AMR have been discussed, including integrated control of antibiotic usage and primary sources of ARGs. Knowledge of the factors affecting AMR has the potential to develop effective policies and technologies to minimize its adverse impacts.