Towards more accurate microbial source tracking via non-negative matrix factorization (NMF).

MOTIVATION: The microbiome of a sampled habitat often consists of microbial communities from various sources, including potential contaminants. Microbial source tracking (MST) can be used to discern the contribution of each source to the observed microbiome data, thus enabling the identification and tracking of microbial communities within a sample. Therefore, MST has various applications, from monitoring microbial contamination in clinical labs to tracing the source of pollution in environmental samples. Despite promising results in MST development, there is still room for improvement, particularly for applications where precise quantification of each source's contribution is critical. RESULTS: In this study, we introduce a novel tool called SourceID-NMF towards more precise microbial source tracking. SourceID-NMF utilizes a non-negative matrix factorization (NMF) algorithm to trace the microbial sources contributing to a target sample. By leveraging the taxa abundance in both available sources and the target sample, SourceID-NMF estimates the proportion of available sources present in the target sample. To evaluate the performance of SourceID-NMF, we conducted a series of benchmarking experiments using simulated and real data. The simulated experiments mimic realistic yet challenging scenarios for identifying highly similar sources, irrelevant sources, unknown sources, low abundance sources, and noise sources. The results demonstrate the superior accuracy of SourceID-NMF over existing methods. Particularly, SourceID-NMF accurately estimated the proportion of irrelevant and unknown sources while other tools either over- or under-estimated them. In addition, the noise sources experiment also demonstrated the robustness of SourceID-NMF for MST. AVAILABILITY AND IMPLEMENTATION: SourceID-NMF is available online at https://github.com/ZiyiHuang0708/SourceID-NMF.

AccuVIR: an ACCUrate VIRal genome assembly tool for third-generation sequencing data.

MOTIVATION: RNA viruses tend to mutate constantly. While many of the variants are neutral, some can lead to higher transmissibility or virulence. Accurate assembly of complete viral genomes enables the identification of underlying variants, which are essential for studying virus evolution and elucidating the relationship between genotypes and virus properties. Recently, third-generation sequencing platforms such as Nanopore sequencers have been used for real-time virus sequencing for Ebola, Zika, coronavirus disease 2019, etc. However, their high per-base error rate prevents the accurate reconstruction of the viral genome. RESULTS: In this work, we introduce a new tool, AccuVIR, for viral genome assembly and polishing using error-prone long reads. It can better distinguish sequencing errors from true variants based on the key observation that sequencing errors can disrupt the gene structures of viruses, which usually have a high density of coding regions. Our experimental results on both simulated and real third-generation sequencing data demonstrated its superior performance on generating more accurate viral genomes than generic assembly or polish tools. AVAILABILITY AND IMPLEMENTATION: The source code and the documentation of AccuVIR are available at https://github.com/rainyrubyzhou/AccuVIR. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

WDNE: an integrative graphical model for inferring differential networks from multi-platform gene expression data with missing values.

The mechanisms controlling biological process, such as the development of disease or cell differentiation, can be investigated by examining changes in the networks of gene dependencies between states in the process. High-throughput experimental methods, like microarray and RNA sequencing, have been widely used to gather gene expression data, which paves the way to infer gene dependencies based on computational methods. However, most differential network analysis methods are designed to deal with fully observed data, but missing values, such as the dropout events in single-cell RNA-sequencing data, are frequent. New methods are needed to take account of these missing values. Moreover, since the changes of gene dependencies may be driven by certain perturbed genes, considering the changes in gene expression levels may promote the identification of gene network rewiring. In this study, a novel weighted differential network estimation (WDNE) model is proposed to handle multi-platform gene expression data with missing values and take account of changes in gene expression levels. Simulation studies demonstrate that WDNE outperforms state-of-the-art differential network estimation methods. When applied WDNE to infer differential gene networks associated with drug resistance in ovarian tumors, cell differentiation and breast tumor heterogeneity, the hub genes in the estimated differential gene networks can provide important insights into the underlying mechanisms. Furthermore, a Matlab toolbox, differential network analysis toolbox, was developed to implement the WDNE model and visualize the estimated differential networks.

Reconstructing viral haplotypes using long reads.

MOTIVATION: Most RNA viruses lack strict proofreading during replication. Coupled with a high replication rate, some RNA viruses can form a virus population containing a group of genetically related but different haplotypes. Characterizing the haplotype composition in a virus population is thus important to understand viruses' evolution. Many attempts have been made to reconstruct viral haplotypes using next-generation sequencing (NGS) reads. However, the short length of NGS reads cannot cover distant single-nucleotide variants, making it difficult to reconstruct complete or near-complete haplotypes. Given the fast developments of third-generation sequencing technologies, a new opportunity has arisen for reconstructing full-length haplotypes with long reads. RESULTS: In this work, we developed a new tool, RVHaplo to reconstruct haplotypes for known viruses from long reads. We tested it rigorously on both simulated and real viral sequencing data and compared it against other popular haplotype reconstruction tools. The results demonstrated that RVHaplo outperforms the state-of-the-art tools for viral haplotype reconstruction from long reads. Especially, RVHaplo can reconstruct the rare (1% abundance) haplotypes that other tools usually missed. AVAILABILITY AND IMPLEMENTATION: The source code and the documentation of RVHaplo are available at https://github.com/dhcai21/RVHaplo. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

HaploDMF: viral haplotype reconstruction from long reads via deep matrix factorization.

MOTIVATION: Lacking strict proofreading mechanisms, many RNA viruses can generate progeny with slightly changed genomes. Being able to characterize highly similar genomes (i.e. haplotypes) in one virus population helps study the viruses' evolution and their interactions with the host/other microbes. High-throughput sequencing data has become the major source for characterizing viral populations. However, the inherent limitation on read length by next-generation sequencing makes complete haplotype reconstruction difficult. RESULTS: In this work, we present a new tool named HaploDMF that can construct complete haplotypes using third-generation sequencing (TGS) data. HaploDMF utilizes a deep matrix factorization model with an adapted loss function to learn latent features from aligned reads automatically. The latent features are then used to cluster reads of the same haplotype. Unlike existing tools whose performance can be affected by the overlap size between reads, HaploDMF is able to achieve highly robust performance on data with different coverage, haplotype number and error rates. In particular, it can generate more complete haplotypes even when the sequencing coverage drops in the middle. We benchmark HaploDMF against the state-of-the-art tools on simulated and real sequencing TGS data on different viruses. The results show that HaploDMF competes favorably against all others. AVAILABILITY AND IMPLEMENTATION: The source code and the documentation of HaploDMF are available at https://github.com/dhcai21/HaploDMF. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Strongyloides stercoralis hyperinfection syndrome mimicking pseudomembranous enteritis, complicated by Escherichia coli bacteremia and Pneumocystis jirovecii pneumonia in a patient after immunosuppressive therapy: a case report.

BACKGROUND: Strongyloidiasis, caused by Strongyloides stercoralis (S. stercoralis), is endemic worldwide, especially in countries with warm and humid climates. Strongyloides stercoralis hyperinfection syndrome (SHS) is an extremely serious manifestation of strongyloidiasis, which results from an acute exacerbation of auto-infection and is often fatal. CASE PRESENTATION: We present a case of SHS mimicking pseudomembranous enteritis with a final definitive diagnosis of a triple infection including S. stercoralis, Escherchia coli (E. coli) and Pneumocytis jirovecii (P. jirovecii) that occurred in a microscopic polyangiitis (MPA) patient after immunosuppressive therapy. SHS, together with E. coli bacteremia and Pneumocytis jirovecii pneumonia (PJP) in the same patient, is rare in clinical practice, which is first reported worldwide, to our knowledge. After the diagnosis was confirmed, the treatment protocol was quickly adjusted; however, the patient's life could not be saved. CONCLUSION: This case reminds us of the necessity to consider strongyloidiasis as a differential diagnosis in immunocompromised populations who live in or have visited to S. stercoralis endemic areas, especially patients with suspected pseudomembranous enteritis, even if stool examination, serological tests, and eosinophilia are negative. For this group, it is advisable to complete the relevant endoscopy and/or PCR as soon as possible. The fundamental solution to prevent this catastrophic outcome is to implement effective preventive measures at multiple levels, including physicians, patients, and relevant authorities.

Pyopneumothorax Caused by Trichomonas tenax and Porphyromonas endodontalis Coinfection in a Patient with Previous Cerebral Infarction: A Case Report and Literature Review.

Background: Even with the advent of NGS and PCR diagnostic tools, cases of chest infections caused by Trichomonas are still very rare. Such pathogens are less likely to be considered by clinicians. These cases frequently involve the pleura and lead to pneumothorax, hydropneumothorax, or pyopneumothorax, making the disease severe. Case Presentation: A 69-year-old man diagnosed with cerebral infarction a year ago sought medical attention for right-sided pyopneumothorax and respiratory failure. The pathogen found in the pleural fluid was highly suspected to be Trichomonas tenax (T. tenax). Pleural fluid mNGS confirmed T. tenax and Porphyromonas endodontalis coinfection. Metronidazole combined with piperacillin tazobactam was administered to counteract infection. Simultaneously, closed chest drainage and thoracoscopic release of pleural adhesions were performed. The patient was cured, discharged from the hospital, and was in good condition after six months of follow-up. Conclusion: When chest infections occur in patients with poor oral hygiene and underlying diseases that may lead to aspiration, the identification of Trichomonas infection should be noted. Early confirmation of the diagnosis often requires mNGS and PCR. Metronidazole is essentially effective against Trichomonas, and medical thoracoscopy can be used to manage pleural conditions if necessary.

Successful treatment of Talaromyces marneffei pneumonia in a HIV-negative renal transplantation recipient: A case report.

RATIONALE: Talaromyces marneffei causes life-threatening opportunistic fungal infections in immunocompromised patients. It often has a poorer prognosis in non-human immunodeficiency virus (HIV)-infected than in HIV-infected individuals because of delayed diagnosis and improper treatment. PATIENT CONCERNS: A 51-year-old man presented with complaints of pyrexia, cough, and expectoration that had lasted for 15 day. This patient has been taking anti-rejection medication since kidney transplant in 2011. DIAGNOSIS: T marneffei pneumonia; post renal transplantation; renal insufficiency; hypertension. INTERVENTIONS: Intravenous moxifloxacin was administered on admission. After the etiology was established, moxifloxacin was discontinued and replaced with voriconazole. The tacrolimus dose was adjusted based on the blood concentration of tacrolimus and voriconazole. OUTCOMES: The patient was successfully treated and followed-up without recurrence for 1 year. LESSONS: A high degree of caution should be maintained for the possibility of T marneffei infection in immunodeficient non-HIV patients who live in or have traveled to T marneffei endemic areas. Early diagnosis and appropriate treatment can prevent progression of T marneffei infection and achieve a cure. Metagenomic next-generation sequencing (mNGS) can aid the physician in reaching an early pathogenic diagnosis. Close monitoring of tacrolimus and voriconazole blood levels during treatment remains a practical approach at this time.

Portulaca Oleracea-associated oxalate nephropathy complicated with an ANCA-positive acute renal injury: A case report.

Oxalate nephropathy is a rare disease that can lead to acute kidney injury (AKI). In clinical practice, as renal biopsy is required for diagnosis, physicians often do not have sufficient understanding of this disease. When AKI is associated with positive blood anti-neutrophil cytoplasmic antibodies (ANCA), a diagnosis of renal injury due to ANCA-associated vasculitis is likely to be made, leading to treatment with immunosuppressive therapy. A case of AKI after eating a large quantity of Portulaca oleracea is reported. While blood P-ANCA was positive, both urine proteinuria and urine occult blood were negative. Renal biopsy was performed and identified an acute tubulointerstitial injury: disc-shaped crystals were seen in the lumen of renal tubules that demonstrated birefringence under polarized light, and an oxalate nephropathy was therefore diagnosed. Typical histological changes of an ANCA-associated vasculitis with renal injury such as cellulose-like necrosis and crescent formation were not present. After the patient stopped eating P. oleracea, and following rehydration and hemodialysis, renal function returned to normal. In patients with AKI, the secondary causes of hyperoxalemia should be sought and attention paid to excluding an oxalate nephropathy. In patients with AKI who are ANCA-positive, it is prudent to complete the renal pathological diagnostic process before assuming that the renal injury is caused by an ANCA-associated vasculitis, and before starting hormone and immunosuppressive therapy.

VirStrain: a strain identification tool for RNA viruses.

Viruses change constantly during replication, leading to high intra-species diversity. Although many changes are neutral or deleterious, some can confer on the virus different biological properties such as better adaptability. In addition, viral genotypes often have associated metadata, such as host residence, which can help with inferring viral transmission during pandemics. Thus, subspecies analysis can provide important insights into virus characterization. Here, we present VirStrain, a tool taking short reads as input with viral strain composition as output. We rigorously test VirStrain on multiple simulated and real virus sequencing datasets. VirStrain outperforms the state-of-the-art tools in both sensitivity and accuracy.

Relationship between Acute Respiratory Tract Infection and the Serum 25(OH) D3 Level in Chronic Kidney Disease Patients and Its Prevention and Treatment.

Observational studies and randomized controlled studies propose that vitamin D plays a significant role in preventing acute respiratory tract infection (RTI); however, results are inconsistent and the optimal serum 25-hydroxyvitamin D (25-OH-D3) concentration remains unknown. This study explores the risk factors associated with acute RTI in patients with chronic kidney disease (CKD) and analyzes its correlation with serum 25-OH-D3 levels, to provide appropriate preventive treatment measures for CKD patients complicated with acute RTI. Seventy cases of CKD patients treated in the department of nephrology of Jiangxi Provincial People's Hospital are recruited as the research objects and divided into a control group (CKD without RTI) and an observation group (CKD with RTI), with 35 cases in each group. The laboratory indexes and serum 25-OH-D3 levels are compared between the two groups. The area under the receiver operating characteristic curve (ROC) of 25-OH-D3 in the diagnosis of CKD patients complicated with RTI is 0.892, and the standard error is 0.038. The glomerular filtration rates (GFR) are 48.32 ± 9.87 mL/min and 50.18 ± 20.71 mL/min in the control group and the experimental group, respectively, with no statistical significance between the two groups (P > 0.05). The serum 25-OH-D3 content in the control group (35.08 ± 6.2 nmol/L) is dramatically higher than that in the observation group (20.71 ± 5.87 nmol/L) (P < 0.05). The proportion of patients with diabetes mellitus (DM) in the control group and observation group is 25.71% and 68.57%, respectively, with a considerable difference (P < 0.05). In the control group and the experimental group, the proportion of patients with oral vitamin D receptor agonists is 54.29% and 11.43%, respectively, and the difference is significant (P < 0.05). Results show that the serum 25-OH-D3 level is highly correlated with the occurrence of RTI in CKD patients. In addition, it is related to patients' age, DM, and vitamin D receptor agonists.

A case of triple infection including strongyloides stercoralis in a microscopic polyangiitis patient.

We present the case of a microscopic polyangiitis (MPA) patient who developed strongyloidiasis, nocardia and citrobacter freundii (CF) infection after corticosteroides and immunosuppressant therapy. When digestive, respiratory or other system symptoms consecutively occur in a immunocompromised host who lives in tropical or temperate zone and have close contact with soil, we should take strongyloidiasis into consideration despite absence of eosinophilia. Mixed infection with nocardia cannot be easily excluded. It is essential to search for the etiology proof with multiple approaches positively and repeatedly.

Inferring Differential Networks by Integrating Gene Expression Data With Additional Knowledge.

Evidences increasingly indicate the involvement of gene network rewiring in disease development and cell differentiation. With the accumulation of high-throughput gene expression data, it is now possible to infer the changes of gene networks between two different states or cell types via computational approaches. However, the distribution diversity of multi-platform gene expression data and the sparseness and high noise rate of single-cell RNA sequencing (scRNA-seq) data raise new challenges for existing differential network estimation methods. Furthermore, most existing methods are purely rely on gene expression data, and ignore the additional information provided by various existing biological knowledge. In this study, to address these challenges, we propose a general framework, named weighted joint sparse penalized D-trace model (WJSDM), to infer differential gene networks by integrating multi-platform gene expression data and multiple prior biological knowledge. Firstly, a non-paranormal graphical model is employed to tackle gene expression data with missing values. Then we propose a weighted group bridge penalty to integrate multi-platform gene expression data and various existing biological knowledge. Experiment results on synthetic data demonstrate the effectiveness of our method in inferring differential networks. We apply our method to the gene expression data of ovarian cancer and the scRNA-seq data of circulating tumor cells of prostate cancer, and infer the differential network associated with platinum resistance of ovarian cancer and anti-androgen resistance of prostate cancer. By analyzing the estimated differential networks, we find some important biological insights about the mechanisms underlying platinum resistance of ovarian cancer and anti-androgen resistance of prostate cancer.