Interaction Between SARS-CoV-2 and Pathogenic Bacteria.

The novel human coronavirus, Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2), which results in the coronavirus disease 2019 (COVID-19), has caused a serious threat to global public health. Therefore, many studies are performed on the causes and prevalence of this disease and the possible co-occurrence of the infection with other viral and bacterial pathogens is investigated. Respiratory infections predispose patients to co-infections and these lead to increased disease severity and mortality. Numerous types of antibiotics have been employed for the prevention and treatment of bacterial co-infection and secondary bacterial infections in patients with a SARS-CoV-2 infection. Although antibiotics do not directly affect SARS-CoV-2, viral respiratory infections often result in bacterial pneumonia. It is possible that some patients die from bacterial co-infection rather than virus itself. Therefore, bacterial co-infection and secondary bacterial infection are considered critical risk factors for the severity and mortality rates of COVID-19. In this review, we will summarize the bacterial co-infection and secondary bacterial infection in some featured respiratory viral infections, especially COVID-19.

Metagenomics characterization of respiratory viral RNA pathogens in children under five years with severe acute respiratory infection in the Free State, South Africa.

Prompt detection of viral respiratory pathogens is crucial in managing respiratory infection including severe acute respiratory infection (SARI). Metagenomics next-generation sequencing (mNGS) and bioinformatics analyses remain reliable strategies for diagnostic and surveillance purposes. This study evaluated the diagnostic utility of mNGS using multiple analysis tools compared with multiplex real-time PCR for the detection of viral respiratory pathogens in children under 5 years with SARI. Nasopharyngeal swabs collected in viral transport media from 84 children admitted with SARI as per the World Health Organization definition between December 2020 and August 2021 in the Free State Province, South Africa, were used in this study. The obtained specimens were subjected to mNGS using the Illumina MiSeq system, and bioinformatics analysis was performed using three web-based analysis tools; Genome Detective, One Codex and Twist Respiratory Viral Research Panel. With average reads of 211323, mNGS detected viral pathogens in 82 (97.6%) of the 84 patients. Viral aetiologies were established in nine previously undetected/missed cases with an additional bacterial aetiology (Neisseria meningitidis) detected in one patient. Furthermore, mNGS enabled the much needed viral genotypic and subtype differentiation and provided significant information on bacterial co-infection despite enrichment for RNA viruses. Sequences of nonhuman viruses, bacteriophages, and endogenous retrovirus K113 (constituting the respiratory virome) were also uncovered. Notably, mNGS had lower detectability rate for severe acute respiratory syndrome coronavirus 2 (missing 18/32 cases). This study suggests that mNGS, combined with multiple/improved bioinformatics tools, is practically feasible for increased viral and bacterial pathogen detection in SARI, especially in cases where no aetiological agent could be identified by available traditional methods.

Metagenomics of gut microbiome for migratory seagulls in Kunming city revealed the potential public risk to human health.

BACKGROUND: Seagull as a migratory wild bird has become most popular species in southwest China since 1980s. Previously, we analyzed the gut microbiota and intestinal pathogenic bacteria configuration for this species by using 16S rRNA sequencing and culture methods. To continue in-depth research on the gut microbiome of migratory seagulls, the metagenomics, DNA virome and RNA virome were both investigated for their gut microbial communities of abundance and diversity in this study. RESULTS: The metagenomics results showed 99.72% of total species was bacteria, followed by viruses, fungi, archaea and eukaryota. In particular, Shigella sonnei, Escherichia albertii, Klebsiella pneumonia, Salmonella enterica and Shigella flexneri were the top distributed taxa at species level. PCoA, NMDS, and statistics indicated some drug resistant genes, such as adeL, evgS, tetA, PmrF, and evgA accumulated as time went by from November to January of the next year, and most of these genes were antibiotic efflux. DNA virome composition demonstrated that Caudovirales was the most abundance virus, followed by Cirlivirales, Geplafuvirales, Petitvirales and Piccovirales. Most of these phages corresponded to Enterobacteriaceae and Campylobacteriaceae bacterial hosts respectively. Caliciviridae, Coronaviridae and Picornaviridae were the top distributed RNA virome at family level of this migratory animal. Phylogenetic analysis indicated the sequences of contigs of Gammacoronavirus and Deltacoronavirus had highly similarity with some coronavirus references. CONCLUSIONS: In general, the characteristics of gut microbiome of migratory seagulls were closely related to human activities, and multiomics still revealed the potential public risk to human health.

Bacterial and viral etiology of acute respiratory infection among the Forcibly Displaced Myanmar Nationals (FDMNs) in fragile settings in Cox's Bazar- a prospective case-control study.

The leading infectious cause of death in children worldwide is lower acute respiratory infection (LARI), particularly pneumonia. We enrolled a total of 538 acute respiratory infection (ARI) cases according to WHO criteria and age-sex matched 514 controls in the Forcibly Displaced Myanmar National (FDMN) refugee camps in Cox's Bazar, Bangladesh, between June 2018 and March 2020 to investigate the role of bacteria, viruses, and their co-infection patterns and observe Streptococcus pneumoniae (S. pneumoniae) serotype distribution. According to the etiological findings, children ≤5 years of age have a higher bacterial positivity (90%) and viral positivity (34%) in nasopharyngeal samples (NPS) compared to those >5 years of age, in both ARI cases as well as for the control group. Among the bacteria, S. pneumoniae was predominant in both cases and controls (85% and 88%). Adenovirus (ADV)(34), influenza virus A and B (IFV-A, B)(32,23), and respiratory syncytial virus (RSV)(26) were detected as the highest number among the viruses tested for the ARI cases. The total number of viruses was also found higher in ≤5 years of age group. Within this group, positive correlation was observed between bacteria and viruses but negative correlation was observed between bacteria. Both single and co-infection for viruses were found higher in the case group than the control group. However, co-infection was significantly high for Streptococcus aureus (S. aureus) and Haemophilus influenzae b (H. influenza b) (p<0.05). Additionally, semi-quantitative bacterial and viral load was found higher for the ARI cases over control considering Cycle threshold (Ct)≤30. Pathogen identification from blood specimens was higher by qRT-PCR than blood culture (16% vs 5%, p<0.05). In the S. pneumoniae serotype distribution, the predominant serotypes in ARI cases were 23F, 19A, 16F, 35B, 15A, 20 and 10F, while 11A, 10A, 34, 35A and 13 serotypes were predominant in the control group. Pathogen correlation analysis showed RSV positively correlated with human metapneumovirus (HMPV), S. aureus and H. influenza b while S. pneumoniae was negatively correlated with other pathogens in ≤5 years age group of ARI cases. However, in >5 years age group, S. aureus and H. influenza b were positively correlated with IFVs, and S. pneumoniae was positively correlated with HMPV and ADV. Logistic regression data for viruses suggested among the respondents in cases were about 4 times more likely to be RSV positive than the control. Serotype distribution showed 30% for PCV10 serotypes, 41% for PCV13 and 59% for other serotypes. Also, among the 40 serotypes of S. pneumoniae tested, the serotypes 22F, Sg24, 9V, 38, 8, and 1 showed strong positive correlation with viruses in the case group whereas in the control group, it was predominant for serotypes 14, 38, 17F and 39 ARI cases were prevalent mostly in monsoon, post-monsoon, and winter periods, and peaked in September and October. Overall these region-specific etiological data and findings, particularly for crisis settings representing the FDMNs in Cox's Bazar, Bangladesh, is crucial for disease management and disease prevention control as well as immunization strategies more generally in humanitarian crisis settings.

Characterization of oral bacterial and fungal microbiome in recovered COVID-19 patients.

COVID-19 has emerged as a global pandemic, challenging the world's economic and health systems. Human oral microbiota comprises the second largest microbial community after the gut microbiota and is closely related to respiratory tract infections; however, oral microbiomes of patients who have recovered from COVID-19 have not yet been thoroughly studied. Herein, we compared the oral bacterial and fungal microbiota after clearance of SARS-CoV-2 in 23 COVID-19 recovered patients to those of 29 healthy individuals. Our results showed that both bacterial and fungal diversity were nearly normalized in recovered patients. The relative abundance of some specific bacteria and fungi, primarily opportunistic pathogens, decreased in recovered patients (RPs), while the abundance of butyrate-producing organisms increased in these patients. Moreover, these differences were still present for some organisms at 12 months after recovery, indicating the need for long-term monitoring of COVID-19 patients after virus clearance.

CRISPR­based diagnostic approaches: Implications for rapid management of future pandemics (Review).

Sudden viral outbreaks have increased in the early part of the 21st century, such as those of severe acute respiratory syndrome coronavirus (SARS­CoV), Middle East respiratory syndrome corona virus, and SARS­CoV­2, owing to increased human access to wildlife habitats. Therefore, the likelihood of zoonotic transmission of human­associated viruses has increased. The emergence of severe acute respiratory syndrome coronavirus 2 in China and its spread worldwide within months have highlighted the need to be ready with advanced diagnostic and antiviral approaches to treat newly emerging diseases with minimal harm to human health. The gold­standard molecular diagnostic approaches currently used are time­consuming, require trained personnel and sophisticated equipment, and therefore cannot be used as point­of­care devices for widespread monitoring and surveillance. Clustered regularly interspaced short palindromic repeats (CRISPR)­associated (Cas) systems are widespread and have been reported in bacteria, archaea and bacteriophages. CRISPR­Cas systems are organized into CRISPR arrays and adjacent Cas proteins. The detection and in­depth biochemical characterization of class 2 type V and VI CRISPR­Cas systems and orthologous proteins such as Cas12 and Cas13 have led to the development of CRISPR­based diagnostic approaches, which have been used to detect viral diseases and distinguish between serotypes and subtypes. CRISPR­based diagnostic approaches detect human single nucleotide polymorphisms in samples from patients with cancer and are used as antiviral agents to detect and destroy viruses that contain RNA as a genome. CRISPR­based diagnostic approaches are likely to improve disease detection methods in the 21st century owing to their ease of development, low cost, reduced turnaround time, multiplexing and ease of deployment. The present review discusses the biochemical properties of Cas12 and Cas13 orthologs in viral disease detection and other applications. The present review expands the scope of CRISPR­based diagnostic approaches to detect diseases and fight viruses as antivirals.

A lung-specific mutational signature enables inference of viral and bacterial respiratory niche.

Exposure to different mutagens leaves distinct mutational patterns that can allow inference of pathogen replication niches. We therefore investigated whether SARS-CoV-2 mutational spectra might show lineage-specific differences, dependent on the dominant site(s) of replication and onwards transmission, and could therefore rapidly infer virulence of emergent variants of concern (VOCs). Through mutational spectrum analysis, we found a significant reduction in G>T mutations in the Omicron variant, which replicates in the upper respiratory tract (URT), compared to other lineages, which replicate in both the URT and lower respiratory tract (LRT). Mutational analysis of other viruses and bacteria indicates a robust, generalizable association of high G>T mutations with replication within the LRT. Monitoring G>T mutation rates over time, we found early separation of Omicron from Beta, Gamma and Delta, while mutational patterns in Alpha varied consistent with changes in transmission source as social restrictions were lifted. Mutational spectra may be a powerful tool to infer niches of established and emergent pathogens.

Mapping human pathogens in wastewater using a metatranscriptomic approach.

The monitoring of cities' wastewaters for the detection of potentially pathogenic viruses and bacteria has been considered a priority during the COVID-19 pandemic to monitor public health in urban environments. The methodological approaches frequently used for this purpose include deoxyribonucleic acid (DNA)/Ribonucleic acid (RNA) isolation followed by quantitative polymerase chain reaction (qPCR) and reverse transcription (RT)‒qPCR targeting pathogenic genes. More recently, the application of metatranscriptomic has opened opportunities to develop broad pathogenic monitoring workflows covering the entire pathogenic community within the sample. Nevertheless, the high amount of data generated in the process requires an appropriate analysis to detect the pathogenic community from the entire dataset. Here, an implementation of a bioinformatic workflow was developed to produce a map of the detected pathogenic bacteria and viruses in wastewater samples by analysing metatranscriptomic data. The main objectives of this work was the development of a computational methodology that can accurately detect both human pathogenic virus and bacteria in wastewater samples. This workflow can be easily reproducible with open-source software and uses efficient computational resources. The results showed that the used algorithms can predict potential human pathogens presence in the tested samples and that active forms of both bacteria and virus can be identified. By comparing the computational method implemented in this study to other state-of-the-art workflows, the implementation analysis was faster, while providing higher accuracy and sensitivity. Considering these results, the processes and methods to monitor wastewater for potential human pathogens can become faster and more accurate. The proposed workflow is available at https://github.com/waterpt/watermonitor and can be implemented in currently wastewater monitoring programs to ascertain the presence of potential human pathogenic species.

Detecting Melanocortin 1 Receptor Gene's SNPs by CRISPR/enAsCas12a.

Beyond its powerful genome-editing capabilities, the CRISPR/Cas system has opened up a new era of molecular diagnostics due to its highly specific base recognition and trans-cleavage activity. However, most CRISPR/Cas detection systems are mainly used to detect nucleic acids of bacteria or viruses, while the application of single nucleotide polymorphism (SNP) detection is limited. The MC1R SNPs were investigated by CRISPR/enAsCas12a and are not limited to the protospacer adjacent motif (PAM) sequence in vitro. Specifically, we optimized the reaction conditions, which proved that the enAsCas12a has a preference for divalent magnesium ion (Mg2+) and can effectively distinguish the genes with a single base difference in the presence of Mg2+, and the Melanocortin l receptor (MC1R) gene with three kinds of SNP sites (T305C, T363C, and G727A) was quantitatively detected. Since the enAsCas12a is not limited by PAM sequence in vitro, the method shown here can extend this extraordinary CRISPR/enAsCas12a detection system to other SNP targets, thus providing a general SNP detection toolbox.

Prevalence of SARS-COV-2 and other respiratory pathogens among a Jordanian subpopulation during Delta-to-Omicron transition: Winter 2021/2022.

Acute respiratory tract infections (ARTIs) during the winter months are associated with higher morbidity and mortality compared to other seasons of the year, with children below five, elderly, and immunocompromised patients being the most susceptible. Influenza A and B viruses, rhinovirus, coronaviruses, respiratory syncytial virus, adenovirus, and parainfluenza viruses, are the most frequently identified causes of viral ARTIs. In addition, the emergence of SARS-CoV-2 in 2019 provided an additional viral cause of ARTIs. The aim of this study was to provide an overview of the epidemiological status of upper respiratory infections, their main causative agents, and reported clinical presentation in the winter months of 2021, during two important surges of COVID-19 in Jordan. Nasopharyngeal samples were collected from 339 symptomatic patients during the period from December 2021 to March 2022, followed by nucleic acid isolation using a Viral RNA/DNA extraction Kit. The causative virus species associated with the patient's respiratory symptoms was determined utilizing a multiplex real-time PCR targeting 21 viruses, 11 bacteria, and a single fungus. SARS-CoV-2 was identified in 39.2% of the patients (n = 133/339). A total of 15 different pathogens were also identified as co-infections among these 133 patients (n = 67/133). SARS-CoV-2-Bacterial coinfections (37.6%, n = 50/133) were the most frequent, with Bordetella species being the most common, followed by Staphylococcus aureus, and H.influenzae type B. Viral coinfection rate was 27.8% (n = 37/133), with Influenza B virus and Human bocavirus being the most common. In Conclusion, Both SARS-CoV-2, influenza B virus, and Bordetella accounted for the majority of infections in patients with URTI during the winter months of 2021-2022. Interestingly, more than 50% of the patients with symptoms of URTIs were confirmed to have a coinfection with two or more respiratory pathogens, with SARS-CoV-2 and Bordetella coinfection being most predominant.

U.S. scientists brace for greater scrutiny of risky research.

Expert panel recommends broader reviews of research involving pathogens or toxins that could have "dual use".

SARS-CoV-2 infection alters the gut microbiome in diabetes patients: A cross-sectional study from Bangladesh.

Populations of different South Asian nations including Bangladesh reportedly have a high risk of developing diabetes in recent years. This study aimed to investigate the differences in the gut microbiome of COVID-19-positive participants with or without type 2 diabetes mellitus (T2DM) compared with healthy control subjects. Microbiome data of 30 participants with T2DM were compared with 22 age-, sex-, and body mass index (BMI)-matched individuals. Clinical features were recorded while fecal samples were collected aseptically from the participants. Amplicon-based (16S rRNA) metagenome analyses were employed to explore the dysbiosis of gut microbiota and its correlation with genomic and functional features in COVID-19 patients with or without T2DM. Comparing the detected bacterial genera across the sample groups, 98 unique genera were identified, of which 9 genera had unique association with COVID-19 T2DM patients. Among different bacterial groups, Shigella (25%), Bacteroides (23.45%), and Megamonas (15.90%) had higher mean relative abundances in COVID-19 patients with T2DM. An elevated gut microbiota dysbiosis in T2DM patients with COVID-19 was observed while some metabolic functional changes correlated with bidirectional microbiome dysbiosis between diabetes and non-diabetes humans gut were also found. These results further highlight the possible association of COVID-19 infection that might be linked with alteration of gut microbiome among T2DM patients.

Analysis of 16S rRNA Gene Sequence of Nasopharyngeal Exudate Reveals Changes in Key Microbial Communities Associated with Aging.

Functional or compositional perturbations of the microbiome can occur at different sites, of the body and this dysbiosis has been linked to various diseases. Changes in the nasopharyngeal microbiome are associated to patient's susceptibility to multiple viral infections, supporting the idea that the nasopharynx may be playing an important role in health and disease. Most studies on the nasopharyngeal microbiome have focused on a specific period in the lifespan, such as infancy or the old age, or have other limitations such as low sample size. Therefore, detailed studies analyzing the age- and sex-associated changes in the nasopharyngeal microbiome of healthy people across their whole life are essential to understand the relevance of the nasopharynx in the pathogenesis of multiple diseases, particularly viral infections. One hundred twenty nasopharyngeal samples from healthy subjects of all ages and both sexes were analyzed by 16S rRNA sequencing. Nasopharyngeal bacterial alpha diversity did not vary in any case between age or sex groups. Proteobacteria, Firmicutes, Actinobacteria, and Bacteroidetes were the predominant phyla in all the age groups, with several sex-associated. Acinetobacter, Brevundimonas, Dolosigranulum, Finegoldia, Haemophilus, Leptotrichia, Moraxella, Peptoniphilus, Pseudomonas, Rothia, and Staphylococcus were the only 11 bacterial genera that presented significant age-associated differences. Other bacterial genera such as Anaerococcus, Burkholderia, Campylobacter, Delftia, Prevotella, Neisseria, Propionibacterium, Streptococcus, Ralstonia, Sphingomonas, and Corynebacterium appeared in the population with a very high frequency, suggesting that their presence might be biologically relevant. Therefore, in contrast to other anatomical areas such as the gut, bacterial diversity in the nasopharynx of healthy subjects remains stable and resistant to perturbations throughout the whole life and in both sexes. Age-associated abundance changes were observed at phylum, family, and genus levels, as well as several sex-associated changes probably due to the different levels of sex hormones present in both sexes at certain ages. Our results provide a complete and valuable dataset that will be useful for future research aiming for studying the relationship between changes in the nasopharyngeal microbiome and susceptibility to or severity of multiple diseases.

Nasal Microbiome in COVID-19: A Potential Role of Corynebacterium in Anosmia.

The evolution and the development of the symptoms of Coronavirus disease 19 (COVID-19) are due to different factors, where the microbiome plays a relevant role. The possible relationships between the gut, lung, nasopharyngeal, and oral microbiome with COVID-19 have been investigated. We analyzed the nasal microbiome of both positive and negative SARS-CoV-2 individuals, showing differences in terms of bacterial composition in this niche of respiratory tract. The microbiota solution A (Arrow Diagnostics) was used to cover the hypervariable V1-V3 regions of the bacterial 16S rRNA gene. MicrobAT Suite and MicrobiomeAnalyst program were used to identify the operational taxonomic units (OTUs) and to perform the statistical analysis, respectively. The main taxa identified in nasal microbiome of COVID-19 patients and in Healthy Control subjects belonged to three distinct phyla: Proteobacteria (HC = 14%, Cov19 = 35.8%), Firmicutes (HC = 28.8%, Cov19 = 30.6%), and Actinobacteria (HC = 56.7%, Cov19 = 14.4%) with a relative abundance > 1% in all groups. A significant reduction of Actinobacteria in Cov19 group compared to controls (P < 0.001, FDR = 0.01) was found. The significant reduction of Actinobacteria was identified in all taxonomic levels down to the genus (P < 0.01) using the ANOVA test. Indeed, a significantly reduced relative abundance of Corynebacterium was found in the patients compared to healthy controls (P = 0.001). Reduced abundance of Corynebacterium has been widely associated with anosmia, a common symptom of COVID-19 as suffered from our patients. Contrastingly, the Corynebacterium genus was highly represented in the nasal mucosa of healthy subjects. Further investigations on larger cohorts are necessary to establish functional relationships between nasal microbiota content and clinical features of COVID-19.

Enrichment of antibiotic resistant genes and pathogens in face masks from coastal environments.

Face masks (FMs) are essential to limit the spread of the coronavirus during pandemic, a considerable of which are accumulated on the coast. However, limited is known about the microbial profile in the biofilm of the face masks (so-called plastisphere) and the impacts of face masks on the surrounding environments. We herein performed face mask exposures to coastal sediments and characterized the microbial community and the antibiotic resistome. We detected 64 antibiotic-resistance genes (ARGs) and 12 mobile gene elements (MGEs) in the plastisphere. Significant enrichments were found in the relative abundance of total ARGs in the plastisphere compared to the sediments. In detail, the relative abundance of tetracycline, multidrug, macrolide-lincosamide-streptogramin B (MLSB), and phenicol-resistant genes had increased by 5-10 times. Moreover, the relative abundance of specific hydrocarbonoclastic bacteria (e.g., Polycyclovorans sp.), pathogens (e.g., Pseudomonas oleovorans), and total MGEs significantly increased in the sediments after face mask exposure, which was congruent with the alteration of pH value and metal concentrations in the microcosms. Our study demonstrated the negative impacts of FMs on coastal environments regardless of the profiles of ARGs or pathogens. These findings improved the understanding of the ecological risks of face masks and underlined the importance of beach cleaning.

Airborne antibiotic resistome and human health risk in railway stations during COVID-19 pandemic.

Antimicrobial resistance is recognized as one of the greatest public health concerns. It is becoming an increasingly threat during the COVID-19 pandemic due to increasing usage of antimicrobials, such as antibiotics and disinfectants, in healthcare facilities or public spaces. To explore the characteristics of airborne antibiotic resistome in public transport systems, we assessed distribution and health risks of airborne antibiotic resistome and microbiome in railway stations before and after the pandemic outbreak by culture-independent and culture-dependent metagenomic analysis. Results showed that the diversity of airborne antibiotic resistance genes (ARGs) decreased following the pandemic, while the relative abundance of core ARGs increased. A total of 159 horizontally acquired ARGs, predominantly confering resistance to macrolides and aminoglycosides, were identified in the airborne bacteria and dust samples. Meanwhile, the abundance of horizontally acquired ARGs hosted by pathogens increased during the pandemic. A bloom of clinically important antibiotic (tigecycline and meropenem) resistant bacteria was found following the pandemic outbreak. 251 high-quality metagenome-assembled genomes (MAGs) were recovered from 27 metagenomes, and 86 genera and 125 species were classified. Relative abundance of ARG-carrying MAGs, taxonomically assigned to genus of Bacillus, Pseudomonas, Acinetobacter, and Staphylococcus, was found increased during the pandemic. Bayesian source tracking estimated that human skin and anthropogenic activities were presumptive resistome sources for the public transit air. Moreover, risk assessment based on resistome and microbiome data revealed elevated airborne health risks during the pandemic.

Enhance antibiotic resistance and human health risks in aerosols during the COVID-19 pandemic.

Aerosols are an important route for the transmission of antibiotic resistance genes (ARGs). Since the 2019 (COVID-19) pandemic, the large-scale use of disinfectants has effectively prevented the spread of environmental microorganisms, but studies regarding the antibiotic resistance of airborne bacteria remain limited. This study focused on four functional urban areas (commercial areas, educational areas, residential areas and wastewater treatment plant) to study the variations in ARG abundances, bacterial community structures and risks to human health during the COVID-19 pandemic in aerosol. The results indicated the abundance of ARGs during the COVID-19 period were up to approximately 13-fold greater than before the COVID-19 period. Large-scale disinfection resulted in a decrease in total bacterial abundance. However, chlorine-resistant bacteria tended to be survived. Among the four functional areas, the diversity and abundance of aerosol bacteria were highest in commercial aera. Antibiotic susceptibility assays suggested elevated resistance of isolated bacteria to several tested antibiotics due to disinfection exposure. The potential exposure risks of ARGs to human health were 2 times higher than before the COVID-19 pandemic, and respiratory intake was the main exposure route. The results highlighted the elevated antibiotic resistance of bacteria in aerosols that were exposed to disinfectants after the COVID-19 pandemic. This study provides theoretical guidance for the rational use of disinfectants and control of antimicrobial resistance.

Exposure to benzalkonium chloride disinfectants promotes antibiotic resistance in sewage sludge microbiomes.

Disinfectants are routinely used in human environments to control and prevent the transmission of microbial disease, and this is particularly true during the current COVID-19 crisis. However, it remains unclear whether the increased disinfectant loadings to wastewater treatment plants facilitate the dissemination of antibiotic resistance genes (ARGs) in sewage sludge microbiomes. Here, we investigated the impacts of benzalkonium chlorides (BACs), widely used disinfectants, on ARGs profiles and microbial community structures in sewage sludge by using high-throughput quantitative PCR and Illumina sequencing. A total of 147 unique ARGs and 39 mobile genetic elements (MGEs) were detected in all sewage sludge samples. Our results show that exposure to BACs disinfectants at environmentally relevant concentrations significantly promotes both the diversity and absolute abundance of ARGs in sludge microbiomes, indicating the co-selection of ARGs by BACs disinfectants. The enrichment of ARGs abundance varied from 2.15-fold to 3.63-fold compared to controls. In addition, BACs exposure significantly alters bacterial and protistan communities, resulting in dysbiosis of the sludge microbiota. The Mantel test and Procrustes analysis confirm that bacterial communities are significantly correlated with ARGs profiles under BACs treatments. The structural equation model explains 83.8 % of the total ARGs variation and further illustrates that the absolute abundance of MGEs exerts greater impacts on the variation of absolute abundance of ARGs than microbial communities under BACs exposure, suggesting BACs may promote antibiotic resistance by enhancing the horizontal gene transfer of ARGs across sludge microbiomes. Collectively, our results provide new insights into the proliferation of antibiotic resistance through disinfectant usage during the pandemic and highlight the necessity to minimize the environmental release of disinfectants into the non-target environment for combating antibiotic resistance.

Massive sequencing of the V3-V4 hypervariable region of bronchoalveolar lavage from patients with COVID-19 and VAP reveals the collapse of the pulmonary microbiota.

Background. The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic is a predisposing factor for the development of healthcare-associated infections, of which ventilator-associated pneumonia (VAP) is one.Hypothesis. VAP is caused by ESKAPE bacteria and other pathogens not detected by microbiological culture.Aim. To elucidate the bacterial pathogens of severe coronavirus disease 2019 (COVID-19) and VAP patients by massive sequencing and to predict their degree of relationship with the age and sex of the patients.Methods. Analysis of ribosomal libraries of the V3-V4 hypervariable region obtained by Illumina sequencing of bronchoalveolar lavages from COVID-19 and VAP (first wave) patients from Hospital Juárez de México.Results. Acinetobacter and Pseudomonas were the main bacterial genera in the bronchoalveolar lavages (BALs) analysed. Other members of the ESKAPE group, such as Enterococcus and Klebsiella, were also identified. Taxonomic composition per patient showed that non-ESKAPE genera were present with significant relative abundances, such as Prevotella, Stenotrophomas, Enterococcus, Mycoplasma, Serratia and Corynebacterium. Kruskal-Wallis analysis proved that VAP acquisition is an adverse event that is not influenced by the sex and age of COVID-19 patients.Discussion. Metagenomic findings in COVID-19/VAP patients highlight the importance of implementing comprehensive microbiological diagnostics by including alternative tools for the detection of the causal agents of healthcare-associated infections (HAIs).Conclusions. Timely identification of bacteria 'not sought' in diagnostic bacteriology laboratories will allow specific and targeted treatments. Implications for the restricted diagnosis of VAP causative agents in COVID-19 patients and the presence of pathogens not detected by classical microbiology are analysed and discussed.

Evaluation of pre-treated healthcare wastes during COVID-19 pandemic reveals pathogenic microbiota, antibiotics residues, and antibiotic resistance genes against beta-lactams.

The disposal of healthcare waste without prior elimination of pathogens and hazardous contaminants has negative effects on the environment and public health. This study aimed to profile the complete microbial community and correlate it with the antibiotic compounds identified in microwave pre-treated healthcare wastes collected from three different waste operators in Peninsular Malaysia. The bacterial and fungal compositions were determined via amplicon sequencing by targeting the full-length 16S rRNA gene and partial 18S with full-length ITS1-ITS2 regions, respectively. The antibiotic compounds were characterized using high-throughput spectrometry. There was significant variation in bacterial and fungal composition in three groups of samples, with alpha- (p-value = 0.04) and beta-diversity (p-values <0.006 and < 0.002), respectively. FC samples were found to acquire more pathogenic microorganisms than FA and FV samples. Paenibacillus and unclassified Bacilli genera were shared among three groups of samples, meanwhile, antibiotic-resistant bacteria Proteus mirabilis, Enterococcus faecium, and Enterococcus faecalis were found in modest quantities. A total of 19 antibiotic compounds were discovered and linked with the microbial abundance detected in the healthcare waste samples. The principal component analysis demonstrated a positive antibiotic-bacteria correlation for genera Pseudomonas, Aerococcus, Comamonas, and Vagococcus, while the other bacteria were negatively linked with antibiotics. Nevertheless, deep bioinformatic analysis confirmed the presence of blaTEM-1 and penP which are associated with the production of class A beta-lactamase and beta-lactam resistance pathways. Microorganisms and contaminants, which serve as putative indicators in healthcare waste treatment evaluation revealed the ineffectiveness of microbial inactivation using the microwave sterilization method. Our findings suggested that the occurrence of clinically relevant microorganisms, antibiotic contaminants, and associated antibiotic resistance genes (ARGs) represent environmental and human health hazards when released into landfills via ARGs transmission.