Baseline circulating tumour DNA and total metabolic tumour volume as early outcome predictors in aggressive large B-cell lymphoma. A real-world 112-patient cohort.

Approximately 20%-50% of patients with large B-cell lymphoma (LBCL) experience poor outcomes. We aimed to evaluate the combined prognostic value of circulating tumour DNA (ctDNA) and total metabolic tumour volume (TMTV) in LBCL. This observational single-centre study included 112 newly diagnosed LBCL patients, receiving R-CHOP/R-CHOP-like chemotherapies. CtDNA load was calculated following next-generation sequencing of cell-free DNA (cfDNA) using a targeted 40-gene lymphopanel. TMTV was measured using a fully automated artificial intelligence-based method for lymphoma lesion segmentation. CtDNA was detected in cfDNA samples from 95 patients with a median concentration of 3.15 log haploid genome equivalents per mL. TMTV measurements were available for 102 patients. The median TMTV was 501 mL. High ctDNA load (>3.57 log hGE/mL) or high TMTV (>200 mL) were associated with shorter 1-year PFS (44% vs. 83%, p < 0.001 and 64% vs. 97%, p = 0.002, respectively). When combined, three prognostic groups were identified. The shortest PFS was observed when both TMTV and ctDNA load were high (p < 0.001). Even with a short follow up, combining ctDNA load with TMTV improved the risk stratification of patients with aggressive LBCL. In the near future, very high-risk patients could benefit from CAR T-cell therapy or bispecific antibodies as first-line treatments.

Viral genomic, metagenomic and human transcriptomic characterization and prediction of the clinical forms of COVID-19.

COVID-19 is characterized by respiratory symptoms of various severities, ranging from mild upper respiratory signs to acute respiratory failure/acute respiratory distress syndrome associated with a high mortality rate. However, the pathophysiology of the disease is largely unknown. Shotgun metagenomics from nasopharyngeal swabs were used to characterize the genomic, metagenomic and transcriptomic features of patients from the first pandemic wave with various forms of COVID-19, including outpatients, patients hospitalized not requiring intensive care, and patients in the intensive care unit, to identify viral and/or host factors associated with the most severe forms of the disease. Neither the genetic characteristics of SARS-CoV-2, nor the detection of bacteria, viruses, fungi or parasites were associated with the severity of pulmonary disease. Severe pneumonia was associated with overexpression of cytokine transcripts activating the CXCR2 pathway, whereas patients with benign disease presented with a T helper "Th1-Th17" profile. The latter profile was associated with female gender and a lower mortality rate. Our findings indicate that the most severe cases of COVID-19 are characterized by the presence of overactive immune cells resulting in neutrophil pulmonary infiltration which, in turn, could enhance the inflammatory response and prolong tissue damage. These findings make CXCR2 antagonists, in particular IL-8 antagonists, promising candidates for the treatment of patients with severe COVID-19.

Novel SARS-CoV-2 Variant Derived from Clade 19B, France.

We report a novel severe acute respiratory syndrome coronavirus 2 variant derived from clade 19B (HMN.19B variant or Henri Mondor variant). This variant is characterized by the presence of 18 amino acid substitutions, including 7-8 substitutions in the spike protein and 2 deletions. These variants actively circulate in different regions of France.

Assessment of Bacterial Colonization of Intracranial Pressure Transducers: A Prospective Study.

OBJECTIVES: Cerebral infections related to the presence of an intraparenchymal intracranial pressure transducer (ICPT) are rare. We assessed the incidence of ICPT-related infections and colonization using culture, molecular biology, and electron microscopy. METHODS: All consecutive patients in a neurosurgical intensive care unit who had an ICPT inserted between March 2017 and February 2018 were prospectively included. Presence of colonization on the ICPTs was assessed after removal using culture, scanning electron microscopy (SEM), and next-generation sequencing (NGS). RESULTS: Fifty-three ICPTs (53 patients), indwelling for a median of 4 (range 3-7) days, were studied. Median patient follow-up was 3 months. SEM, microbial culture, and NGS were performed for 91%, 79%, and 72% of ICPTs, respectively; 28 ICPTs (53%) were assessed using all three techniques. No patient developed ICPT-related infection. Microbial cultures were positive for two of the ICPTs (5%); colonization was identified on all ICPTs using NGS and SEM. Mature biofilm was observed on 35/48 (73%) of ICPTs. A median of 10 (8-12) operational taxonomic units were identified for each ICPT, most being of environmental origin. There was no association between biofilm maturity and antimicrobial treatment or duration of ICPT insertion. Antimicrobial treatment was associated with decreased alpha and beta-diversity (p = 0.01). CONCLUSIONS: We observed no ICPT-related cerebral infections although colonization was identified on all ICPTs using NGS and SEM. Mature biofilm was the main bacterial lifestyle on the ICPTs.

Fatal Encephalitis Caused by Cristoli Virus, an Emerging Orthobunyavirus, France.

We report the discovery of a new orthobunyavirus, Cristoli virus, by means of shotgun metagenomics. The virus was identified in an immunodepressed patient with fatal encephalitis. Full-length genome sequencing revealed high-level expression of a virulence factor, possibly explaining the severity of the infection. The patient's recent history suggests circulation in France.

Fatal Measles Inclusion-Body Encephalitis in Adult with Untreated AIDS, France.

We report a fatal case of measles inclusion-body encephalitis occurring in a woman from Romania with AIDS. After an extensive but unsuccessful diagnostic evaluation, a pan-pathogen shotgun metagenomic approach revealed a measles virus infection. We identified no mutations previously associated with neurovirulence.

Artificial Intelligence Methods and Models for Retro-Biosynthesis: A Scoping Review.

Retrosynthesis aims to efficiently plan the synthesis of desirable chemicals by strategically breaking down molecules into readily available building block compounds. Having a long history in chemistry, retro-biosynthesis has also been used in the fields of biocatalysis and synthetic biology. Artificial intelligence (AI) is driving us toward new frontiers in synthesis planning and the exploration of chemical spaces, arriving at an opportune moment for promoting bioproduction that would better align with green chemistry, enhancing environmental practices. In this review, we summarize the recent advancements in the application of AI methods and models for retrosynthetic and retro-biosynthetic pathway design. These techniques can be based either on reaction templates or generative models and require scoring functions and planning strategies to navigate through the retrosynthetic graph of possibilities. We finally discuss limitations and promising research directions in this field.

neo4jsbml: import systems biology markup language data into the graph database Neo4j.

Systems Biology Markup Language (SBML) has emerged as a standard for representing biological models, facilitating model sharing and interoperability. It stores many types of data and complex relationships, complicating data management and analysis. Traditional database management systems struggle to effectively capture these complex networks of interactions within biological systems. Graph-oriented databases perform well in managing interactions between different entities. We present neo4jsbml, a new solution that bridges the gap between the Systems Biology Markup Language data and the Neo4j database, for storing, querying and analyzing data. The Systems Biology Markup Language organizes biological entities in a hierarchical structure, reflecting their interdependencies. The inherent graphical structure represents these hierarchical relationships, offering a natural and efficient means of navigating and exploring the model's components. Neo4j is an excellent solution for handling this type of data. By representing entities as nodes and their relationships as edges, Cypher, Neo4j's query language, efficiently traverses this type of graph representing complex biological networks. We have developed neo4jsbml, a Python library for importing Systems Biology Markup Language data into a Neo4j database using a user-defined schema. By leveraging Neo4j's graphical database technology, exploration of complex biological networks becomes intuitive and information retrieval efficient. Neo4jsbml is a tool designed to import Systems Biology Markup Language data into a Neo4j database. Only the desired data is loaded into the Neo4j database. neo4jsbml is user-friendly and can become a useful new companion for visualizing and analyzing metabolic models through the Neo4j graphical database. neo4jsbml is open source software and available at https://github.com/brsynth/neo4jsbml.

Case Report: Cerebral Nocardiosis Caused by Nocardia cyriacigeorgica Detected by Metagenomics in an Apparently Immunocompetent Patient.

We report a case of meningoencephalitis due to Nocardia cyriacigeorgica diagnosed with metagenomics, while all the standard methods were negative. This diagnosis made adaptation of antimicrobial treatment possible and led to the discovery of a rare, acquired immunodeficiency syndrome.

Fusion Gene Detection and Quantification by Asymmetric Capture Sequencing (aCAP-Seq).

Several fusion genes such as BCR::ABL1, FIP1L1::PDGFRA, and PML::RARA are now efficiently targeted by specific therapies in patients with leukemia. Although these therapies have significantly improved patient outcomes, leukemia relapse and progression remain clinical concerns. Most myeloid next-generation sequencing (NGS) panels do not detect or quantify these fusions. It therefore remains difficult to decipher the clonal architecture and dynamics of myeloid malignancy patients, although these factors can affect clinical decisions and provide pathophysiologic insights. An asymmetric capture sequencing strategy (aCAP-Seq) and a bioinformatics algorithm (HmnFusion) were developed to detect and quantify MBCR::ABL1, µBCR::ABL1, PML::RARA, and FIP1L1::PDGFRA fusion genes in an NGS panel targeting 41 genes. One-hundred nineteen DNA samples derived from 106 patients were analyzed by conventional methods at diagnosis or on follow-up and were sequenced with this NGS myeloid panel. The specificity and sensitivity of fusion detection by aCAP-Seq were 100% and 98.1%, respectively, with a limit of detection estimated at 0.1%. Fusion quantifications were linear from 0.1% to 50%. Breakpoint locations and sequences identified by NGS were concordant with results obtained by Sanger sequencing. Finally, this new sensitive and cost-efficient NGS method allowed integrated analysis of resistant chronic myeloid leukemia patients and thus will be of interest to elucidate the mutational landscape and clonal architecture of myeloid malignancies driven by these fusion genes at diagnosis, relapse, or progression.

Prospective Comparison Between Shotgun Metagenomics and Sanger Sequencing of the 16S rRNA Gene for the Etiological Diagnosis of Infections.

Bacteriological diagnosis is traditionally based on culture. However, this method may be limited by the difficulty of cultivating certain species or by prior exposure to antibiotics, which justifies the resort to molecular methods, such as Sanger sequencing of the 16S rRNA gene (Sanger 16S). Recently, shotgun metagenomics (SMg) has emerged as a powerful tool to identify a wide range of pathogenic microorganisms in numerous clinical contexts. In this study, we compared the performance of SMg to Sanger 16S for bacterial detection and identification. All patients' samples for which Sanger 16S was requested between November 2019 and April 2020 in our institution were prospectively included. The corresponding samples were tested with a commercial 16S semi-automated method and a semi-quantitative pan-microorganism DNA- and RNA-based SMg method. Sixty-seven samples from 64 patients were analyzed. Overall, SMg was able to identify a bacterial etiology in 46.3% of cases (31/67) vs. 38.8% (26/67) with Sanger 16S. This difference reached significance when only the results obtained at the species level were compared (28/67 vs. 13/67). This study provides one of the first evidence of a significantly better performance of SMg than Sanger 16S for bacterial detection at the species level in patients with infectious diseases for whom culture-based methods have failed. This technology has the potential to replace Sanger 16S in routine practice for infectious disease diagnosis.

Analysis of Microbiota and Mycobiota in Fungal Ball Rhinosinusitis: Specific Interaction between Aspergillus fumigatus and Haemophilus influenza?

Fungal ball (FB) rhinosinusitis (RS) is the main type of non-invasive fungal RS. Despite positive direct examination (DE) of biopsies, culture remains negative in more than 60% of cases. The aim of the study was to evaluate the performance/efficacy of targeted metagenomics (TM) to analyze microbiota and mycobiota in FB and find microbial associations. Forty-five sinus biopsies from patients who underwent surgery for chronic RS were included. After DE and culture, DNA was extracted, then fungal ITS1-ITS2 and bacterial V3-V4 16S rDNA loci were sequenced (MiSeqTM Illumina). Operational taxonomic units (OTUs) were defined via QIIME and assigned to SILVA (16S) and UNITE (ITS) databases. Statistical analyses were performed using SHAMAN. Thirty-eight patients had FB and seven had non-fungal rhinosinusitis (NFRS). DE and culture of FB were positive for fungi in 97.3 and 31.6% of patients, respectively. TM analysis of the 38 FB yielded more than one fungal genus in 100% of cases, with Aspergillus in 89.5% (34/38). Haemophilus was over-represented in FB with >1000 reads/sample in 47.3% (18/38) compared to NFRS (p < 0.001). TM allowed fungal identification in biopsies with negative culture. Haemophilus was associated with FB. Pathogenesis could result from fungi-bacteria interactions in a mixed biofilm-like structure.

Macrophage autophagy protects against hepatocellular carcinogenesis in mice.

Autophagy is a lysosomal degradation pathway of cellular components that regulates macrophage properties. Macrophages are critically involved in tumor growth, metastasis, angiogenesis and immune suppression. Here, we investigated whether macrophage autophagy may protect against hepatocellular carcinoma (HCC). Experiments were performed in mice with deletion of the autophagy gene Atg5 in the myeloid lineage (ATG5Mye-/- mice) and their wild-type (WT) littermates. As compared to WT, ATG5Mye-/- mice were more susceptible to diethylnitrosamine (DEN)-induced hepatocarcinogenesis, as shown by enhanced tumor number and volume. Moreover, DEN-treated ATG5Mye-/- mice exhibited compromised immune cell recruitment and activation in the liver, suggesting that macrophage autophagy invalidation altered the antitumoral immune response. RNA sequencing showed that autophagy-deficient macrophages sorted from DEN mice are characterized by an enhanced expression of immunosuppressive markers. In vitro studies demonstrated that hepatoma cells impair the autophagy flux of macrophages and stimulate their expression of programmed cell death-ligand 1 (PD-L1), a major regulator of the immune checkpoint. Moreover, pharmacological activation of autophagy reduces hepatoma cell-induced PD-L1 expression in cultured macrophages while inhibition of autophagy further increases PD-L1 expression suggesting that autophagy invalidation in macrophages induces an immunosuppressive phenotype. These results uncover macrophage autophagy as a novel protective pathway regulating liver carcinogenesis.

Benchmark of thirteen bioinformatic pipelines for metagenomic virus diagnostics using datasets from clinical samples.

INTRODUCTION: Metagenomic sequencing is increasingly being used in clinical settings for difficult to diagnose cases. The performance of viral metagenomic protocols relies to a large extent on the bioinformatic analysis. In this study, the European Society for Clinical Virology (ESCV) Network on NGS (ENNGS) initiated a benchmark of metagenomic pipelines currently used in clinical virological laboratories. METHODS: Metagenomic datasets from 13 clinical samples from patients with encephalitis or viral respiratory infections characterized by PCR were selected. The datasets were analyzed with 13 different pipelines currently used in virological diagnostic laboratories of participating ENNGS members. The pipelines and classification tools were: Centrifuge, DAMIAN, DIAMOND, DNASTAR, FEVIR, Genome Detective, Jovian, MetaMIC, MetaMix, One Codex, RIEMS, VirMet, and Taxonomer. Performance, characteristics, clinical use, and user-friendliness of these pipelines were analyzed. RESULTS: Overall, viral pathogens with high loads were detected by all the evaluated metagenomic pipelines. In contrast, lower abundance pathogens and mixed infections were only detected by 3/13 pipelines, namely DNASTAR, FEVIR, and MetaMix. Overall sensitivity ranged from 80% (10/13) to 100% (13/13 datasets). Overall positive predictive value ranged from 71-100%. The majority of the pipelines classified sequences based on nucleotide similarity (8/13), only a minority used amino acid similarity, and 6 of the 13 pipelines assembled sequences de novo. No clear differences in performance were detected that correlated with these classification approaches. Read counts of target viruses varied between the pipelines over a range of 2-3 log, indicating differences in limit of detection. CONCLUSION: A wide variety of viral metagenomic pipelines is currently used in the participating clinical diagnostic laboratories. Detection of low abundant viral pathogens and mixed infections remains a challenge, implicating the need for standardization and validation of metagenomic analysis for clinical diagnostic use. Future studies should address the selective effects due to the choice of different reference viral databases.

Fitness-associated substitutions following failure of direct-acting antivirals assessed by deep sequencing of full-length hepatitis C virus genomes.

BACKGROUND: In hepatitis C virus (HCV) infection, treatment failure is generally associated with the selection of resistance-associated substitutions (RAS) conferring reduced susceptibility to direct-acting antiviral (DAA) drugs. Resistant variants continue to replicate after the end of treatment with potential for transmission. This may result from the selection of "fitness-associated substitutions". AIM: To characterise potential "fitness-associated substitutions" in patients infected with genotype 3a failing DAA drugs METHODS: By means of shotgun metagenomics, we sequenced full-length HCV genomes at treatment initiation and at virological relapse in eight patients infected with genotype 3a with cirrhosis failing sofosbuvir and an NS5A inhibitor. The impact of amino acid changes occurring outside of DAA target regions selected in at least two patients were assessed on the in vitro susceptibility to an NS5A inhibitor and replication capacity. RESULTS: At treatment failure, besides selection of known NS5A RASs, especially Y93H, a large number of amino acid changes was observed outside of DAA target regions. We identified four amino acid positions at which observed changes substantially improved in vitro replication capacity without affecting NS5A inhibitor susceptibility. CONCLUSIONS: This is the first in vivo observation combined with in vitro confirmation of selection of phenotypically characterised "fitness-associated substitutions" together with RASs at the time of sofosbuvir-NS5A inhibitor treatment failure in patients infected with genotype 3a with cirrhosis. Our findings may explain the persistence of resistant HCV variants after treatment in patients who did not achieve sustained virological remission.

Impact and consequences of intensive chemotherapy on intestinal barrier and microbiota in acute myeloid leukemia: the role of mucosal strengthening.

Induction chemotherapy (7 + 3 regimen) remains the gold standard for patients with acute myeloid leukemia (AML) but is responsible for gut damage leading to several complications such as bloodstream infection (BSI). We aimed to investigate the impact of induction chemotherapy on the intestinal barrier of patients with AML and in wild-type mice. Next, we assessed the potential benefit of strengthening the mucosal barrier in transgenic mice releasing a recombinant protein able to reinforce the mucus layer (Tg222). In patients, we observed a decrease of plasma citrulline, which is a marker of the functional enterocyte mass, of short-chain fatty acids and of fecal bacterial load, except for Escherichia coli and Enterococcus spp., which became dominant. Both the α and ß-diversities of fecal microbiota decreased. In wild-type mice, citrulline levels decreased under chemotherapy along with an increase of E. coli and Enterococcus spp load associated with concomitant histologic impairment. By comparison with wild-type mice, Tg222 mice, 3 days after completing chemotherapy, had higher citrulline levels, a faster healing epithelium, and preserved α-diversity of their intestinal microbiota. This was associated with reduced bacterial translocations. Our results highlight the intestinal damage and the dysbiosis induced by the 7 + 3 regimen. As a proof of concept, our transgenic model suggests that strengthening the intestinal barrier is a promising approach to limit BSI and improve AML patients' outcome.