Evaluation of respiratory samples in etiology diagnosis and microbiome characterization by metagenomic sequencing.

BACKGROUND: The application of clinical mNGS for diagnosing respiratory infections improves etiology diagnosis, however at the same time, it brings new challenges as an unbiased sequencing method informing all identified microbiomes in the specimen. METHODS: Strategy evaluation and metagenomic analysis were performed for the mNGS data generated between March 2017 and October 2019. Diagnostic strengths of four specimen types were assessed to pinpoint the more appropriate type for mNGS diagnosis of respiratory infections. Microbiome complexity was revealed between patient cohorts and infection types. A bioinformatic pipeline resembling diagnosis results was built based upon multiple bioinformatic parameters. RESULTS: The positive predictive values (PPVs) for mNGS diagnosing of non-mycobacterium, Nontuberculous Mycobacteria (NTM), and Aspergillus were obviously higher in bronchoalveolar lavage fluid (BALF) demonstrating the potency of BALF in mNGS diagnosis. Lung tissues and sputum were acceptable for diagnosis of the Mycobacterium tuberculosis (MTB) infections. Interestingly, significant taxonomy differences were identified in sufficient BALF specimens, and unique bacteriome and virome compositions were found in the BALF specimens of tumor patients. Our pipeline showed comparative diagnostic strength with the clinical microbiological diagnosis. CONCLUSIONS: To achieve reliable mNGS diagnosis result, BALF specimens for suspicious common infections, and lung tissues and sputum for doubtful MTB infections are recommended to avoid the false results given by the complexed respiratory microbiomes. Our developed bioinformatic pipeline successful helps mNGS data interpretation and reduces manual corrections for etiology diagnosis.

Genome-wide association study of Klebsiella pneumoniae identifies variations linked to carbapenems resistance.

Klebsiella pneumoniae (KP) is one of the microorganisms that can acquire carbapenem-resistance (CR), and few antimicrobial therapy options exist for infections caused by Carbapenem-Resistant KP (CRKP). In recent years, with the increase of carbapenem resistance rates, treating CRKP has become a serious public health threat in clinical practice. We have collected 2,035 clinical KP isolates from a tertiary hospital in China. Whole genome sequencing data coupled with their binary antimicrobial susceptibility testing data were obtained to conduct the genome-wide association study using a bayesian-based method, including single nucleotide polymorphisms (SNPs) and genes. We identified 28 and 37 potential maker genes associated with imipenem and meropenem resistance, respectively. Among which 19 of them were selected in both drugs by genome-wide association study (GWAS), 11 genes among them were simultaneously validated in independent datasets. These genes were likely related to biofilm formation, efflux pump, and DNA repairing. Moreover, we identified 13 significant CR related SNPs in imipenem or meropenem, with one SNP located in the non-coding region and validated in the independent datasets. Our study indicates complex mechanisms of carbapenems resistance and further investigation of CRKP-related factors are warranted to better understand their contributions to carbapenems resistance. These identified biomarkers may provide targets for future drug interventions or treatments.

Large-Scale Genomic Epidemiology of Klebsiella pneumoniae Identified Clone Divergence with Hypervirulent Plus Antimicrobial-Resistant Characteristics Causing Within-Ward Strain Transmissions.

Global dissemination of K. pneumoniae clones poses health hazards to the public. Genomic epidemiology studies with comprehensive data set further revealed clone divergence, showing a high complexity in evolution. Moreover, clones carrying both acquired virulent and antimicrobial-resistant genes emerged and might replace the carbapenem-resistant clones. Co-occurrence of virulence and resistance is emerging. An unbiased collection of 3,061 clinical K. pneumoniae isolates (January 5, 2013 to July 24, 2018) underwent whole-genome sequencing. Pairwise core-genome single-nucleotide polymorphism (cgSNP) distances identified clone divergence and transmission events. A sum of 2,193 nonduplicated genomes clustered into four phenotypically indistinguishable species complexes. 93% (n = 2,035) were KpI with its largest clonal group (CG) being CG11 (n = 406). Three hundred ninety-three were ST11 and three hundred seventy-four carried blaKPC-2. Noticeably, CG11 is divided into two main subclones based on the capsule synthesis K loci (KL). CG11-KL64 showed a clear hypervirulent plus antimicrobial-resistant (hv+AMR) characteristic. Besides, the phylogenetic structure revealed the clone divergence of CG25, and this is the first report with sufficient CG25 genomes to identify the divergence. The outcomes of the hv+AMR CG25 cluster 1 affected patients were poorer (P < 0.05). Moreover, two episodes of strain transmissions were associated with CG25 cluster 1. Other transmissions were associated with ST20 and ST307. Genomic epidemiology identified clone divergence of CG11 and CG25. The hv+AMR subclones pose greater threats on a global scale. Nosocomial transmissions of the high-risk clones raised our concerns about the evolution and transmission of emerging clones among newborns and critically ill patients. IMPORTANCE The convergence of AMR and acquired virulence posing higher risks to the public is a focusing point. With sufficient genomes and genotypes, we successfully identify the convergence in two subclones, the previously reported CG11-KL64, and the newly reported CG25 cluster 1. The novel finding of the CG25 divergence was not only revealed by the phylogenetic tree but also confirmed by the clinical outcome data and the accessory genome patterns. Moreover, the transmission subclones circulated in two clinically important wards highlights the deficiency of infection control program using conventional methods. Without the assistance of whole-genome sequencing, the transmissions of high-risk clones could not be identified.

Characterization of respiratory microbial dysbiosis in hospitalized COVID-19 patients.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a global pandemic of Coronavirus disease 2019 (COVID-19). However, the microbial composition of the respiratory tract and other infected tissues as well as their possible pathogenic contributions to varying degrees of disease severity in COVID-19 patients remain unclear. Between 27 January and 26 February 2020, serial clinical specimens (sputum, nasal and throat swab, anal swab and feces) were collected from a cohort of hospitalized COVID-19 patients, including 8 mildly and 15 severely ill patients in Guangdong province, China. Total RNA was extracted and ultra-deep metatranscriptomic sequencing was performed in combination with laboratory diagnostic assays. We identified distinct signatures of microbial dysbiosis among severely ill COVID-19 patients on broad spectrum antimicrobial therapy. Co-detection of other human respiratory viruses (including human alphaherpesvirus 1, rhinovirus B, and human orthopneumovirus) was demonstrated in 30.8% (4/13) of the severely ill patients, but not in any of the mildly affected patients. Notably, the predominant respiratory microbial taxa of severely ill patients were Burkholderia cepacia complex (BCC), Staphylococcus epidermidis, or Mycoplasma spp. (including M. hominis and M. orale). The presence of the former two bacterial taxa was also confirmed by clinical cultures of respiratory specimens (expectorated sputum or nasal secretions) in 23.1% (3/13) of the severe cases. Finally, a time-dependent, secondary infection of B. cenocepacia with expressions of multiple virulence genes was demonstrated in one severely ill patient, which might accelerate his disease deterioration and death occurring one month after ICU admission. Our findings point to SARS-CoV-2-related microbial dysbiosis and various antibiotic-resistant respiratory microbes/pathogens in hospitalized COVID-19 patients in relation to disease severity. Detection and tracking strategies are needed to prevent the spread of antimicrobial resistance, improve the treatment regimen and clinical outcomes of hospitalized, severely ill COVID-19 patients.

Draft Genome Sequence of a Polymyxin-Resistant Klebsiella pneumoniae Clinical Strain Carrying mcr-8.1 and bla NDM-5.

Carbapenem-resistant Klebsiella pneumoniae (CRKP) is a major threat to global health. Here, we report the draft genome sequence of a Klebsiella pneumoniae clinical strain carrying mcr-8.1 and bla NDM-5.

Longitudinal Study of the Drug Resistance in Klebsiella pneumoniae of a Tertiary Hospital, China: Phenotypic Epidemiology Analysis (2013-2018).

PURPOSE: Multi-drug resistant Klebsiella pneumoniae (MDR KP) is spreading worldwide and has posed a huge medical burden to public health. However, studies on drug resistance surveillance of KP, especially MDR KP, with a large longitudinal sample size in a tertiary hospital are rare. This study aims to investigate phenotypic epidemiology characteristics of 4128 KP isolates in a Chinese tertiary hospital covering a period of 5 years. METHODS: All the KP clinical isolates were retrospectively collected from a tertiary hospital in Hunan province of China from Jan 5, 2013 to Jul 24, 2018. All the isolates were identified by MALDI-TOF MS analysis. Twenty-four antimicrobial agents were tested by antimicrobial susceptibility testing. Fisher exact test and logistic regression were used to analyze the association between clinical factors and antimicrobial non-susceptibility for seven second-choice antimicrobials. RESULTS: A total of 4128 KP isolates were collected in our study. The non-susceptible rates (NSRs) to ertapenem, imipenem and tigecycline increased considerably from 2013 to 2018 (13.6% to 28.6%, 10.1% to 28.9%, 10.8% to 46.5%, respectively). Amikacin presents the lowest NSR among 3 aminoglycosides (3.8-22.8%). The multi-drug NSRs among KP isolates to second-choice antimicrobials (88.6-100%) were higher than to all drugs (68.0%). The NSRs varied significantly among departments and sample sources. Higher ETP/IPM/AK NSRs (39.8/39.7/30.6%) were observed in Intensive Care Unit, and ETP/IPM non-susceptible isolates tended to distribute in cerebrospinal fluid. From 2015 to 2017, the NSRs of ETP, IPM, and AK showed an opposite trend of seasonal fluctuations to SXT. CONCLUSION: Higher multi-drug resistance (MDR) rates were observed in KP isolates to second-choice antimicrobials than to others, among which MDR rates to carbapenems or AK are the highest. A unique pattern of MIC and time distributions of MDR were observed. Clinical factors including gender were correlated with MDR rates of KP. Isolates in ICU and CSF showed higher NSRs in carbapenems which should be paid more attention to, and temporal distribution of NSRs was observed.

Multiple approaches for massively parallel sequencing of SARS-CoV-2 genomes directly from clinical samples.

BACKGROUND: COVID-19 (coronavirus disease 2019) has caused a major epidemic worldwide; however, much is yet to be known about the epidemiology and evolution of the virus partly due to the scarcity of full-length SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) genomes reported. One reason is that the challenges underneath sequencing SARS-CoV-2 directly from clinical samples have not been completely tackled, i.e., sequencing samples with low viral load often results in insufficient viral reads for analyses. METHODS: We applied a novel multiplex PCR amplicon (amplicon)-based and hybrid capture (capture)-based sequencing, as well as ultra-high-throughput metatranscriptomic (meta) sequencing in retrieving complete genomes, inter-individual and intra-individual variations of SARS-CoV-2 from serials dilutions of a cultured isolate, and eight clinical samples covering a range of sample types and viral loads. We also examined and compared the sensitivity, accuracy, and other characteristics of these approaches in a comprehensive manner. RESULTS: We demonstrated that both amplicon and capture methods efficiently enriched SARS-CoV-2 content from clinical samples, while the enrichment efficiency of amplicon outran that of capture in more challenging samples. We found that capture was not as accurate as meta and amplicon in identifying between-sample variations, whereas amplicon method was not as accurate as the other two in investigating within-sample variations, suggesting amplicon sequencing was not suitable for studying virus-host interactions and viral transmission that heavily rely on intra-host dynamics. We illustrated that meta uncovered rich genetic information in the clinical samples besides SARS-CoV-2, providing references for clinical diagnostics and therapeutics. Taken all factors above and cost-effectiveness into consideration, we proposed guidance for how to choose sequencing strategy for SARS-CoV-2 under different situations. CONCLUSIONS: This is, to the best of our knowledge, the first work systematically investigating inter- and intra-individual variations of SARS-CoV-2 using amplicon- and capture-based whole-genome sequencing, as well as the first comparative study among multiple approaches. Our work offers practical solutions for genome sequencing and analyses of SARS-CoV-2 and other emerging viruses.

Risk Factors Associated with Dengue Virus Infection in Guangdong Province: A Community-Based Case-Control Study.

Dengue fever (DF) is a mosquito-borne infectious disease that is now an epidemic in China, Guangdong Province, in particular and presents high incidence rates of DF. Effective preventive measures are critical for controlling DF in China given the absence of a licensed vaccination program in the country. This study aimed to explore the individual risk factors for the dengue virus infection in Guangdong Province and to provide a scientific basis for the future prevention and control of DF. A case-control study including 237 cases and 237 controls was performed. Cases were defined for samples who were IgG-antibody positive or IgM-antibody positive, and willing to participate in the questionnaire survey. Additionally, the controls were selected through frequency matching by age, gender and community information from individuals who tested negative for IgG and IgM and volunteered to become part of the samples. Data were collected from epidemiological questionnaires. Univariate analysis was performed for the preliminary screening of 28 variables that were potentially related to dengue virus infection, and multivariate analysis was performed through unconditioned logistic regression analysis to analyze statistically significant variables. Multivariate analysis revealed two independent risk factors: Participation in outdoor sports (odds ratio (OR) = 1.80, 95% confidence interval (CI) 1.17 to 2.78), and poor indoor daylight quality (OR = 2.27, 95% CI 1.03 to 5.03). Two protective factors were identified through multivariate analysis: 2 occupants per room (OR = 0.43, 95% CI 0.28 to 0.65) or ≥3 occupants per room (OR = 0.45, 95% CI 0.23 to 0.89) and air-conditioner use (OR = 0.46, 95% CI 0.22 to 0.97). The results of this study were conducive for investigating the risk factors for dengue virus infection in Guangdong Province. Effective and efficient strategies for improving environmental protection and anti-mosquito measures must be provided. In addition, additional systematic studies are needed to explore other potential risk factors for DF.

Dengue Infection Spectrum in Guangzhou: A Cross-Sectional Seroepidemiology Study among Community Residents between 2013 and 2015.

The majority of dengue virus infections are asymptomatic, which could potentially facilitate the transmission of dengue fever and increase the percentage of sever dengue fever manifestations. This cross-sectional study explored the sero-prevalence of dengue virus infection in Guangzhou to clarify the infection spectrum. In total, 2085 serum samples were collected from residents of 34 communities. All samples were selected from a 200,000-sample database holding serum collected from community residents living in Liwan and Yuexiu districts of Guangzhou between September 2013 and August 2015, and 17 to 28 individuals of each age group were chosen per month. Dengue immunoglobulin G (IgG) and immunoglobulin M (IgM) antibodies were tested by enzyme-linked immunosorbent assay. Symptomatic infected individuals were identified via follow-up questionnaires. Among 2085 serum samples, anti-dengue IgG and IgM positive rates were 11.80% and 3.98%, respectively. The IgG antibody positive rate increased with age and was higher in poorly educated people than in highly educated people and in married individuals than in single individuals. Approximately 96.71% of dengue virus infections and an estimated 13.68% of the whole population were asymptomatic. Such high asymptomatic-infection rates have an impact on the local spread of dengue fever. Stricter surveillance, such as a network of rapid diagnostic laboratories, screening of residents in the epidemic season, and other integrated control measures are necessary.

FPGA Implementation of the Coupled Filtering Method and the Affine Warping Method.

In ultrasound image analysis, the speckle tracking methods are widely applied to study the elasticity of body tissue. However, "feature-motion decorrelation" still remains as a challenge for the speckle tracking methods. Recently, a coupled filtering method and an affine warping method were proposed to accurately estimate strain values, when the tissue deformation is large. The major drawback of these methods is the high computational complexity. Even the graphics processing unit (GPU)-based program requires a long time to finish the analysis. In this paper, we propose field-programmable gate array (FPGA)-based implementations of both methods for further acceleration. The capability of FPGAs on handling different image processing components in these methods is discussed. A fast and memory-saving image warping approach is proposed. The algorithms are reformulated to build a highly efficient pipeline on FPGA. The final implementations on a Xilinx Virtex-7 FPGA are at least 13 times faster than the GPU implementation on the NVIDIA graphic card (GeForce GTX 580).

On feature motion decorrelation in ultrasound speckle tracking.

Speckle tracking methods refer to motion tracking methods based on speckle patterns in ultrasound images. They are commonly used in ultrasound based elasticity imaging techniques to reveal mechanical properties of tissues for clinical diagnosis. In speckle tracking, feature motion decorrelation exists when speckle patterns are not identical before and after tissue motion and deformation. Feature motion decorrelation violates the underlying assumption of most speckle tracking methods. Consequently, the estimation accuracy of current methods is greatly limited. In this paper, two types of speckle pattern variations, the geometric transformation and the intensity change of speckle patterns, are studied. We show that a coupled filtering method is able to compensate for both types of variations. It provides accurate strain estimations even when tissue deformation or rotation is extremely large. We also show that in most cases, an affine warping method that only compensates for the geometric transformation is able to achieve a similar performance as the coupled filtering method. Feature motion decorrelation in B-mode images is also studied. Finally, we show that in typical elastography studies, speckle tracking methods without modeling local shearing or rotation will fail when tissue deformation is large.