Gilman Kit-Hang Siu’s research while affiliated with The Hong Kong Polytechnic University and other places

A clinical isolate, R131, was isolated from the peritoneal swab of a patient who suffered from ruptured appendicitis with abscess and gangrene in Hong Kong in 2018. Cells are facultatively anaerobic, non-motile, Gram-positive coccobacilli. Colonies were small, grey, semi-translucent, low convex and alpha-haemolytic. The bacterium grew on blood agar but not on Brain Heart Infusion (BHI) and Mueller–Hinton agars. It was negative for catalase, oxidase, indole and aesculin hydrolysis. The initial identification attempts via matrix-assisted laser desorption ionization–time of flight mass spectrometry and 16S rRNA gene sequencing yielded inconclusive results. The 16S rRNA gene analysis showed that R131 shared >99% nucleotide identity with certain uncultured Actinomycetales bacteria. In this retrospective investigation, a complete genome of R131 was constructed, disclosing a DNA G+C content of 64%. Phylogenetic analysis showed that the bacterium was mostly related to Scrofimicrobium canadense WB03_NA08, which was first described in 2020. However, its 16S rRNA gene shared only 94.15% nucleotide identity with that of S. canadense WB03_NA08. Notably, the orthoANI between R131 and S. canadense WB03_NA08 was 67.81%. A pan-genome analysis encompassing R131 and 4 Scrofimicrobium genomes showed 986 core gene clusters shared with the Scrofimicrobium species, along with 601 cloud genes. The average nucleotide identity comparisons within the pan-genome analysis ranged from 59.78 to 62.51% between R131 and the other Scrofimicrobium species. Correspondingly, the dDDH values ranged from 19.20 to 22.30%, while the POCP values spanned from 57.48 to 60.94%. Therefore, a novel species, Scrofimicrobium appendicitidis sp. nov., is proposed. The type strain is R131 T (=JCM 36615 T =LMG 33627 T ).

Introduction Vibrio alginolyticus is a Gram-negative, rod-shaped bacterium belonging to the family of Vibrionaceae, a common pathogen in aquaculture animals, However, studies on its impact on Scylla serrata (mud crabs) are limited. In this study, we isolated V. alginolyticus SWS from dead mud crab during a disease outbreak in a Hong Kong aquaculture farm, which caused up to 70% mortality during summer. Methods Experimental infection and histopathology were used to investigate the pathogenicity of V. alginolyticus SWS in S. serrata and validate Koch’s postulates. Comprehensive whole-genome analysis and phylogenetic analysis antimicrobial susceptibility testing, and biochemical characterization were also performed. Results Our findings showed that V. alginolyticus SWS caused high mortality (75%) in S. serrata with infected individuals exhibiting inactivity, loss of appetite, decolored and darkened hepatopancreas, gills, and opaque muscle in the claw. Histopathological analysis revealed tissue damage and degeneration in the hepatopancreas, gills, and claw muscle suggesting direct and indirect impacts of V. alginolyticus SWS infection. Conclusions This study provides a comprehensive characterization of V. alginolyticus SWS as an emerging pathogen in S. serrata aquaculture. Our findings underscore the importance of ongoing surveillance, early detection, and the development of targeted disease management strategies to mitigate the economic impact of vibriosis outbreaks in mud crab aquaculture.

Objective: This study aimed to characterize the changing landscape of circulating SARS-CoV-2 lineages in the local community of Hong Kong throughout 2022. We examined how adjustments to quarantine arrangements influenced the transmission pattern of Omicron variants in a city with relatively rigorous social distancing measures at that time. Methods: In 2022, a total of 4684 local SARS-CoV-2 genomes were sequenced using the Oxford Nanopore GridION sequencer. SARS-CoV-2 consensus genomes were generated by MAFFT, and the maximum likelihood phylogeny of these genomes was determined using IQ-TREE. The dynamic changes in lineages were depicted in a time tree created by Nextstrain. Statistical analysis was conducted to assess the correlation between changes in the number of lineages and adjustments to quarantine arrangements. Results: By the end of 2022, a total of 83 SARS-CoV-2 lineages were identified in the community. The increase in the number of new lineages was significantly associated with the relaxation of quarantine arrangements (One-way ANOVA, F(5, 47) = 18.233, p < 0.001)). Over time, Omicron BA.5 sub-lineages replaced BA.2.2 and became the predominant Omicron variants in Hong Kong. The influx of new lineages reshaped the dynamics of Omicron variants in the community without fluctuating the death rate and hospitalization rate (One-way ANOVA, F(5, 47) = 2.037, p = 0.091). Conclusion: This study revealed that even with an extended mandatory quarantine period for incoming travelers, it may not be feasible to completely prevent the introduction and subsequent community spread of highly contagious Omicron variants. Ongoing molecular surveillance of COVID-19 remains essential to monitor the emergence of new recombinant variants.

Objective: The study aimed to characterize the changing landscape of circulating SARS-CoV-2 lineages in the local community of Hong Kong throughout 2022. We examined how adjustments to quarantine arrangements influenced the transmission pattern of Omicron variants in a city with relatively rigorous social distancing measures at that time. Methods: In 2022, a total of 4,684 local SARS-CoV-2 genomes were sequenced using the Oxford Nanopore GridION sequencer. SARS-CoV-2 consensus genomes were generated by MAFFT, and the maximum likelihood phylogeny of these genomes were determined using IQ-TREE. The dynamic changes in lineages were depicted in a time tree created by Nextstrain. Statistical analysis was conducted to assess the correlation between changes in the number of lineages and adjustments to quarantine arrangements. Results: By the end of 2022, a total of 83 SARS-CoV-2 lineages were identified in the community. The increase in the number of new lineages was significantly associated with the relaxation of quarantine arrangements (One-way ANOVA, F(5,47)=18.233, p<0.001)). Over time, Omicron BA.5 sub-lineages replaced BA.2.2 and became the predominant Omicron variants in Hong Kong. The influx of new lineages reshaped the dynamics of Omicron variants in the community without fluctuating the death rate and hospitalization rate (One-way ANOVA, F(5,47)=2.037, p=0.091). Conclusion: The study revealed that even with an extended mandatory quarantine period for incoming travelers, it may not be feasible to completely prevent the introduction and subsequent community spread of highly contagious Omicron variants. Ongoing molecular surveillance of COVID-19 remains essential to monitor the emergence of new recombinant variants.

The incidence of isoniazid (INH) resistant Mycobacterium tuberculosis is increasing globally. This study aimed to identify the molecular mechanisms behind the development of INH resistance in M. tuberculosis strains collected from the same patients during the standard course of treatment. Three M. tuberculosis strains were collected from a patient before and during antituberculosis (anti-TB) therapy. The strains were characterized using phenotypic drug susceptibility tests, Mycobacterial Interspersed Repeated Unit-Variable-Number Tandem Repeats (MIRU-VNTR), and whole-genome sequencing (WGS) to identify mutations associated with INH resistance. To validate the role of the novel mutations in INH resistance, the mutated katG genes were electroporated into a KatG-deleted M. tuberculosis strain (GA03). Three-dimensional structures of mutated KatG were modeled to predict their impact on INH binding. The pre-treatment strain was susceptible to INH. However, two INH-resistant strains were isolated from the patient after anti-TB therapy. MIRU-VNTR and WGS revealed that the three strains were clonally identical. A missense mutation (P232L) and a nonsense mutation (Q461Stop) were identified in the katG of the two post-treatment strains, respectively. Transformation experiments showed that katG of the pre-treatment strain restored INH susceptibility in GA03, whereas the mutated katG genes from the post-treatment strains rendered negative catalase activity and INH resistance. The protein model indicated that P232L reduced INH-KatG binding affinity while Q461Stop truncated gene transcription. Our results showed that the two katG mutations, P232L and Q461Stop, accounted for the co-emergence of INH-resistant clones during anti-TB therapy. The inclusion of these mutations in the design of molecular assays could increase the diagnostic performance. IMPORTANCE The evolution of drug-resistant strains of Mycobacterium tuberculosis within the lung lesions of a patient has a detrimental impact on treatment outcomes. This is particularly concerning for isoniazid (INH), which is the most potent first-line antimycobacterial drug. However, the precise genetic factors responsible for drug resistance in patients have not been fully elucidated, with approximately 15% of INH-resistant strains harboring unknown genetic factors. This raises concerns about the emergence of drug-resistant clones within patients, further contributing to the global epidemic of resistance. In this study, we revealed the presence of two novel katG mutations, which emerged independently due to the stress exerted by antituberculosis (anti-TB) treatment on a parental strain. Importantly, we experimentally demonstrated the functional significance of both mutations in conferring resistance to INH. Overall, this research sheds light on the genetic mechanisms underlying the evolution of INH resistance within patients and provides valuable insights for improving diagnostic performance by targeting specific mutations.

An AI-empowered indoor digital contact-tracing system was developed using a centralized architecture and advanced low-energy Bluetooth technologies for indoor positioning, with careful preservation of privacy and data security. We analyzed the contact pattern data from two RCHs and investigated a COVID-19 outbreak in one study site. To evaluate the effectiveness of the system in containing outbreaks with minimal contacts under quarantine, a simulation study was conducted to compare the impact of different quarantine strategies on outbreak containment within RCHs. The significant difference in contact hours between weekdays and weekends was observed for some pairs of RCH residents and staff during the two-week data collection period. No significant difference between secondary cases and uninfected contacts was observed in a COVID-19 outbreak in terms of their demographics and contact patterns. Simulation results based on the collected contact data indicated that a threshold of accumulative contact hours one or two days prior to diagnosis of the index case could dramatically increase the efficiency of outbreak containment within RCHs by targeted isolation of the close contacts. This study demonstrated the feasibility and efficiency of employing an AI-empowered system in indoor digital contact tracing of outbreaks in RCHs in the post-pandemic era.

The prolonged incubation period of traditional culture methods leads to a delay in diagnosing invasive infections. Nanopore 16S rRNA gene sequencing (Nanopore 16S) offers a potential rapid diagnostic approach for directly identifying bacteria in infected body fluids. To evaluate the clinical utility of Nanopore 16S, we conducted a study involving the collection and sequencing of 128 monomicrobial samples, 65 polymicrobial samples, and 20 culture-negative body fluids. To minimize classification bias, taxonomic classification was performed using 3 analysis pipelines: Epi2me, Emu, and NanoCLUST. The result was compared to the culture references. The limit of detection of Nanopore 16S was also determined using simulated bacteremic blood samples. Among the three classifiers, Emu demonstrated the highest concordance with the culture results. It correctly identified the taxon of 125 (97.7%) of the 128 monomicrobial samples, compared to 109 (85.2%) for Epi2me and 102 (79.7%) for NanoCLUST. For the 230 cultured species in the 65 polymicrobial samples, Emu correctly identified 188 (81.7%) cultured species, compared to 174 (75.7%) for Epi2me and 125 (54.3%) for NanoCLUST. Through ROC analysis on the monomicrobial samples, we determined a threshold of relative abundance at 0.058 for distinguishing potential pathogens from background in Nanopore 16S. Applying this threshold resulted in the identification of 107 (83.6%), 117 (91.4%), and 114 (91.2%) correctly detected samples for Epi2me, Emu, and NanoCLUST, respectively, in the monomicrobial samples. Nanopore 16S coupled with Epi2me could provide preliminary results within 6 h. However, the ROC analysis of polymicrobial samples exhibited a random-like performance, making it difficult to establish a threshold. The overall limit of detection for Nanopore 16S was found to be about 90 CFU/ml.

Foodborne pathogens, particularly antimicrobial-resistant (AMR) bacteria, remain a significant threat to global health. Conventional culture-based approaches for detecting infectious agents are limited in scope and time-consuming. Metagenomic sequencing of food products offers a rapid and comprehensive approach to detect pathogenic microbes, including AMR bacteria. In this study, we used nanopore-based metagenomic sequencing to detect pathogenic microbes and antimicrobial resistance genes (ARGs) in 260 food products, including raw meat, sashimi, and ready-to-eat (RTE) vegetables. We identified Clostridium botulinum and Staphylococcus aureus as the predominant foodborne pathogens in the food samples, particularly prevalent in fresh, peeled, and minced foods. Importantly, RTE-vegetables, which harbored Acinetobacter baumannii and Toxoplasma gondii as the dominant foodborne pathogens, displayed the highest abundance of carbapenem resistance genes among the different food types. Exclusive bla CTX-M gene-carrying plasmids were found in both RTE-vegetables and sashimi. Additionally, we assessed the impact of host DNA and sequencing depth on microbial profiling and ARG detection, highlighting the preference for nanopore sequencing over Illumina for ARG detection. A lower sequencing depth of around 25,000 is adequate for effectively profiling bacteria in food samples, whereas a higher sequencing depth of approximately 700,000 is required to detect ARGs. Our workflow provides insights into the development of food safety monitoring tools and can assess the potential risk to human health from foodborne pathogens and ARGs. This approach has the potential to revolutionize the screening of food products and enable more efficient and accurate detection of foodborne pathogens and ARGs, thereby reducing the risks of foodborne illness and improving public health.