Intratumoral microbiota has emerged as a notable factor influencing cancer initiation and progression. However, its composition and functional impact in esophageal squamous cell carcinoma (ESCC) remain largely unexplored. Here, we performed metagenomic sequencing on 119 paired tumor-normal tissues from patients with ESCC and single-cell RNA sequencing on 45 samples to investigate microbe-host interactions. We identified Parvimonas micra (P. micra), an anaerobic oral-derived bacterium, as significantly enriched in tumor tissues and associated with poor prognosis. Moreover, the abundance of P. micra correlated with increased regulatory T cell (Treg cell) infiltration in the ESCC tumor microenvironment. Through cellular and animal experiments, we demonstrate that P. micra promotes tumor growth by secreting p-cresol, a metabolite of amino acid fermentation, which elevates reactive oxygen species levels and induces FOXP3+ Treg differentiation, thereby fostering immunosuppression and tumor growth. Our study establishes a mechanistic link between intratumoral microbiota and the immune microenvironment, highlighting the microbial contribution to ESCC progression and prognosis.

We demonstrated an all-polarization-maintaining (PM), multi-branch optical frequency comb based on an all-fiber configuration. To achieve fiber noise cancellation, we aligned the beat note of the out-of-loop branch with that of the in-loop branch by phase-locking both branches to a common 1550 nm ultra-stable laser. To further assess the out-of-loop frequency instability of the constructed fiber comb, we heterodyned it with another quasi-identical fiber comb. Thanks to effective fiber noise cancellation and a small difference in out-of-loop fiber lengths, the frequency instability of a single comb reached an exceptional level of 2.26 x 10-17 at 1 s and 8.4 x 10-20 at 4000 s.

The respiratory microbiome plays an important role in maintaining human health. Despite the rapid growth of literature and publicly accessible data on the respiratory microbiome, a large-scale, well-curated database is still lacking. Here, we introduced ResMicroDb, a comprehensive database and analysis platform for the human respiratory microbiome. ResMicroDb contains 106 464 samples from 514 projects, spanning 10 sample sites, 72 sample types, and 146 phenotypes. Notably, it includes ~7-fold more respiratory samples than existing multi-body-site resources. To improve the reusability and accessibility of data, a standardized bioinformatics pipeline was employed to generate taxonomic profiles, and 32 metadata fields were manually curated. ResMicroDb also provides 11 908 microbe-disease associations, identified from 132 case-control studies, to deepen the understanding of microbiome-disease relationships. Additionally, ResMicroDb offers three tools for in-depth analysis: "Microbiome Composition" for visualizing taxonomic profiles of user-selected samples; "Sample Similarity Search" for inferring the characteristics of new samples by comparing them to the database based on similarity; and "Cross-study Analysis" for identifying common and specific microbial characteristics across cohorts, phenotypes and sample sites. ResMicroDb serves as a versatile and valuable resource for advancing a broad spectrum of respiratory microbiome research and clinical relevance. ResMicroDb is freely accessed at https://resmicrodb.cncb.ac.cn.

The upper respiratory tract microbiome (URM) influences host susceptibility and respiratory disease outcomes, but its normal temporal dynamics remain poorly understood. We conducted temporal metagenomic profiling of the URM by collecting oropharyngeal swabs from 22 healthy adults at 4-h intervals over 48 h. We identify significant 24-h cyclic variations in microbial composition and biomass, with two predominant oscillation patterns: “evening-peak” and “morning-peak” patterns. Temporal variation introduces substantial shifts in microbial profiles, leading to false positives in differential analyses. Microbial rhythmicity is linked to phenotypic traits such as oxygen and nutrient requirements. Nonetheless, rhythmic patterns differ across individuals, and regression analysis reveals that host identity contributes more substantially to microbial rhythmicity than species identity. Functional pathway analysis based on metagenomic sequencing data shows similar circadian fluctuations. Additionally, although anatomically adjacent, the oral cavity and oropharynx exhibit divergent rhythmic behaviors, highlighting local environmental influences on microbial rhythmicity. These findings reveal previously unrecognized temporal dynamics of the URM and provide a temporal framework for more accurate biomarker discovery.

The net-cavity dispersion critically influences mode-locked pulse properties, yet independent tuning without affecting other parameters is experimentally challenging. By tuning the intracavity fiber length ratio with fixed cavity length and pump power attenuation, we achieve independent, wide-range dispersion tuning in an all polarization-maintaining (PM) nonlinear amplifying loop mirror (NALM) erbium-doped fiber laser , and compare output characteristics across four regimes from normal (+0.012 ps2) to anomalous (-0.005 ps2) dispersion. We find that lasers operating near zero net-cavity dispersion offer significant advantages in both spectral and noise performance, with a free-running carrier-envelope-offset (CEO) frequency linewidth of 21.32 kHz (1-second integration) and a 43-dB signal-to-noise ratio. These results demonstrate the critical role of dispersion management in optimizing comb noise performance and provide practical guidance for the development of lownoise, all-PM NALM Er:fiber frequency combs.

Objective To determine whether HLA-DQ2/8 genotype shapes the human microbiome at strain and functional levels, and whether such effects relate to systemic metabolism and clinical phenotypes in healthy adults. Design We analyzed 60 young adults stratified by HLA-DQ2/8 status (28 carriers, 32 non-carriers). Over 8 weeks, we collected fecal and salivary metagenomes, serum metabolomes, dietary records, and clinical phenotypes. We combined species-level and strain-level analyses of microbiome composition and function, HLA class II binding predictions of microbial gene products, and structural modeling of HLA-DQ– microbial peptide complexes. Results HLA-DQ2/8 carriers showed higher gut microbial α-diversity, elevated Gut Microbiome Health Index, and fewer virulence genes. Gut species composition differed significantly by genotype (PERMANOVA p<0.01), and species-level profiles predicted genotype with high accuracy (LASSO AUC=0.90). Strain-level divergence was identified in 15 gut species, with functional specialization in peptidoglycan, indole, and coenzyme A (CoA) biosynthesis pathways; Blautia obeum was the principal contributor to CoA-related differences. At the gene level, GO enrichment highlighted membrane-associated processes across gut and saliva, suggesting adaptation at the host–microbe interface. Microbial genes with predicted HLA-DQ binding occurred at lower prevalence than non-binders, and AlphaFold3 modeling confirmed haplotype-specific microbial peptide–HLA interactions. Serum metabolomics revealed lower pantothenate in carriers, with reduced HDL-cholesterol, heart rate, neutrophil and basophil counts; HDL-cholesterol correlated positively with pantothenate. Conclusions HLA-DQ2/8 genotype is associated with the adult microbiome at strain and functional levels through antigen-presentation–mediated selection, with systemic signatures in vitamin B5/CoA metabolism and HDL-cholesterol. These findings reveal a genotype– microbiome–host axis in health and motivate larger, multi-ethnic cohorts. What is already known on this subject? What are the new findings? How might it impact on clinical practice in the foreseeable future? ### Competing Interest Statement The authors have declared no competing interest. Youth Innovation Promotion Association of Chinese Academy of Sciences, grant no. 2021097

While Epstein-Barr virus (EBV) infection is ubiquitous globally, a high-risk EBV subtype associated with the extremely high incidence of nasopharyngeal carcinoma (NPC) was found in southern China, but the evolution history of EBV in humans and the origin of this high-risk subtype remains enigmatic. By obtaining one of the largest datasets of EBV genomes across the world, we found that EBV had an evolutionary history matching the out-of-Africa migration of humans. Within the high-risk subtype from southern China, we identified a rapidly expanding clonal strain originating from a recombination event between EBV strains from northern and southern Chinese around 4000 years ago, followed by strong Darwinian evolution with a fitness advantage of 4%. The clonal strain has almost doubled the risk for NPC compared to the high-risk subtype and explained around 66% of the NPCs, representing the highest risk factor for NPC identified so far. Taken together, we unraveled a strong co-evolution history between EBV and humans where human migration and admixture triggered subsequent recombination and expansion of a highly advantageous EBV strain, leading to a cancer epidemic in southern China.

Although public attention to SARS-CoV-2 has waned,the virus continues to cir-culate within the population and contin-ues to mutate and cause periodic surges.Mutations could alter the virus's anti-genic properties,facilitate immune es-cape[1]and lead to persistent prevalence and recurrent outbreaks.Additionally,mutations could potentially enhance the virus's transmissibility and pathogenicity[2,3],thereby posing an ongoing threat to public health.

Microwave sources based on ultrastable lasers and optical frequency combs (OFCs) exhibit ultralow phase noise and ultrahigh-frequency stability, which are important for many applications. Herein, we present a microwave source that is phase-locked to an ultrastable continuous-wave laser, with a relative frequency instability of 7 × 10−16 at 1 s. An Er:fiber-based OFC and an optic-to-electronic converter with low residual noise are employed to confer optical frequency stability on the 9.6 GHz microwave signal. Instead of using the normal cascaded Mach–Zehnder interferometer method, we developed a microwave regeneration method for converting optical pulses into microwave signals to further suppress the additional noise in the optic-to-electronic conversion process. The microwave regeneration method employs an optical-to-microwave phase detector based on a fiber-based Sagnac loop to produce the error signal between a 9.6 GHz dielectric resonator oscillator (DRO) and the OFC. The 9.6 GHz microwave (48th harmonic of the comb’s repetition rate) signal with the frequency stability of the ultrastable laser was achieved using a DRO that was phase-locked to the optical comb. Preliminary evaluations showed that the frequency instability of the frequency synthesizer from the optical to the 9.6 GHz microwave signal was approximately 2 × 10−15 at 1 s, the phase noise was −106 dBc Hz−1 at 1 Hz, and the timing noise was approximately 9 as Hz−1/2 (phase noise approx. −125 dBc Hz−1). The 9.6 GHz signal from the photonic microwave source exhibited a short-term relative frequency instability of 2.1 × 10−15 at 1 s, which is 1.5 times better than the previous results.

High-throughput sequencing technologies generate a vast number of DNA sequence reads simultaneously, which are subsequently analysed using the information contained within these fragmented reads. The assessment of sequencing technology relies on information efficiency, which measures the amount of information entropy produced per sequencing reaction cycle. Here we propose a fuzzy sequencing strategy that exhibits information efficiency more than twice that of currently prevailing cyclic reversible terminator sequencing methods. To validate our approach, we develop a fully functional and high-throughput fuzzy sequencer. This sequencer implements an efficient fluorogenic sequencing-by-synthesis chemistry and we test it across various application scenarios, including copy-number variation detection, non-invasive prenatal testing, transcriptome profiling, mutation genotyping and metagenomic profiling. Our findings demonstrate that the fuzzy sequencing strategy outperforms existing methods in terms of information efficiency and delivers accurate resequencing results with faster turnaround times.

The human microbiome is transmissible between individuals, including pathogens and commensals with metabolic and immune-modulating effects, which could influence susceptibility, severity, and outcomes of both infection and non-infection diseases. However, limited studies of respiratory microbiome transmission within populations have been conducted. Herein, we performed species- and strain-level metagenomic analyses on oropharyngeal (OP) swabs from 1046 healthy urban dwellers across 13 districts, including 111 households with at least two cohabitants, to elucidate the transmission dynamics of the respiratory microbiome within households and communities. We found that geographic districts accounted for the greatest variation in the OP microbiome, with unrelated individuals from the same district showing greater microbiome similarity and higher strain-sharing rates than those from different districts. Cohabitants, especially spouses and siblings, exhibited similar microbial abundances and shared more strains, with 16.7

Metagenomic sequencing for respiratory pathogen detection faces two challenges: efficient host DNA depletion and the representativeness of upper respiratory samples for lower tract infections. In this study, we benchmarked seven host depletion methods, including a new method (F_ase), using bronchoalveolar lavage fluid (BALF), oropharyngeal swab (OP), and mock samples. All methods significantly increased microbial reads, species richness, genes richness, and genome coverage while reduced bacterial biomass, introduced contamination, and altered microbial abundance. Some commensals and pathogens, including Prevotella spp. and Mycoplasma pneumoniae, were significantly diminished. F_ase demonstrated the most balanced performance. High-resolution microbiomes profiling revealed distinct microbial niche preferences and microbiome disparities between the upper and lower respiratory tract. In pneumonia patients, 16.7% of high-abundance species (>1%) in BALF were underrepresented (<0.1%) in OP, highlighting OP's limitations as lower respiratory proxies. This study underscores both the potential and challenges of metagenomic sequencing in advancing microbial ecology and clinical research.

Emerging SARS-CoV-2 sub -lineages like XBB.1.5, XBB.1.16, EG.5, HK.3 (FLip), and XBB.2.3 and the variant BA.2.86 have recently been identified. Understanding the efficacy of current vaccines on these emerging variants is critical. We evaluate the serum neutralization activities of participants who received COVID-19 inactivated vaccine (CoronaVac), those who received the recently approved tetravalent protein vaccine (SCTV01E), or those who had contracted a breakthrough infection with BA.5/BF.7/XBB virus. Neutralization profiles against a broad panel of 30 sub -lineages reveal that BQ.1.1, CH.1.1, and all the XBB sub -lineages exhibit heightened resistance to neutralization compared to previous variants. However, despite their extra mutations, BA.2.86 and the emerging XBB sub -lineages do not demonstrate significantly increased resistance to neutralization over XBB.1.5. Encouragingly, the SCTV01E booster consistently induces higher neutralizing titers against all these variants than breakthrough infection does. Cellular immunity assays also show that the SCTV01E booster elicits a higher frequency of virus -specific memory B cells. Our findings support the development of multivalent vaccines to combat future variants.

The Pearl River Estuary (PRE), with eight outlets supplied by multiple tributaries, is an excellent study area for reconstructing sediment provenance and transport pathways of a multi-sourced sediment-routing system. However, the sediment source to sink dispersal model is less well-known. This study aimed to estimate the PRE sediment budget by comparing the magnetic characteristics of estuarine surface sediments with those of all potential sources. In the bottom sediments of PRE and adjacent region, magnetic minerals, mainly magnetite and hematite, have a characteristic terrigenous signature. Source and sink comparison for magnetic parameters shows that the possible input of southwestern Taiwan rivers can be excluded, whereas the possibility of sediment contribution from nearby rivers, including Han, Rong, and Jiulong rivers, to the estuary could not be ruled out. Quantitative provenance analysis indicates that West River-sourced sediment dominates the western side of the estuary, the East River-sourced sediment is most important in the eastern side of the estuary, whereas sediment supplied by the North River is high only close to the outlets. A mixed-sediment contribution to the estuary is suggested, with a fluvial-dominated sediment input around the west river outlets and a tide-dominated sediment dispersal in the eastern side of the estuary. Overall, our study demonstrates the importance of fingerprinting changes in sediment supply using sediment magnetic properties and provides new insights into the PRE sediment-routing system.

Brazil, Russia, India, China, and South Africa (BRICS) are a group of developing countries with shared economic, healthcare, and scientific interests. These countries navigate multiple syndemics, and the COVID-19 pandemic placed severe strain on already burdened BRICS’ healthcare systems, hampering effective pandemic interventions. Genomic surveillance and molecular epidemiology remain indispensable tools for facilitating informed pandemic intervention. To evaluate the combined manner in which the pandemic unfolded in BRICS countries, we reviewed the BRICS pandemic epidemiological and genomic milestones, which included the first reported cases and deaths, and pharmaceutical and non-pharmaceutical interventions implemented in these countries. To assess the development of genomic surveillance capacity and efficiency over the pandemic, we analyzed the turnaround time from sample collection to data availability and the technologies used for genomic analysis. This data provided information on the laboratory capacities that enable the detection of emerging SARS-CoV-2 variants and highlight their potential for monitoring other pathogens in ongoing public health efforts. Our analyses indicated that BRICS suffered >105.6M COVID-19 infections, resulting in >1.7M deaths. BRICS countries detected intricate genetic combinations of SARS-CoV-2 variants that fueled country-specific pandemic waves. BRICS’ genomic surveillance programs enabled the identification and characterization of the majority of globally circulating Variants of Concern (VOCs) and their descending lineages. Pandemic intervention strategies first implemented by BRICS countries included non-pharmaceutical interventions during the onset of the pandemic, such as nationwide lockdowns, quarantine procedures, the establishment of fever clinics, and mask mandates- which were emulated internationally. Vaccination rollout strategies complemented this, some representing the first of their kind. Improvements in BRICS sequencing and data generation turnaround time facilitated quicker detection of circulating and emerging variants, supported by investments in sequencing and bioinformatic infrastructure. Intra-BRICS cooperation contributed to the ongoing intervention in COVID-19 and other pandemics, enhancing collective capabilities in addressing these health challenges. The data generated continues to inform BRICS-centric pandemic intervention strategies and influences global health matters. The increased laboratory and bioinformatic capacity post-COVID-19 will support the detection of emerging pathogens.

Mid-infrared frequency-comb spectroscopy enables measurement of molecules at megahertz spectral resolution, sub-hertz frequency accuracy, and microsecond acquisition speed. However, the widespread adoption of this technique has been hindered by the complexity and alignment sensitivity of mid-infrared frequency-comb sources. Leveraging the underexplored mid-infrared window of silica fibers presents a promising approach to address these challenges. In this study, we present the first, to the best of our knowledge, experimental demonstration and quantitative numerical description of mid-infrared frequency-comb generation in silica fibers. Our all-silica-fiber frequency comb spans over two octaves (0.8 μm to 3.4 μm) with a power output of 100 mW in the mid-infrared region. The amplified quantum noise is suppressed using four-cycle (25 fs) driving pulses, with the carrier-envelope offset frequency exhibiting a signal-to-noise ratio of 40 dB and a free-running bandwidth of 90 kHz. Our developed model provides quantitative guidelines for mid-infrared frequency-comb generation in silica fibers, enabling all-fiber frequency-comb spectroscopy in diverse fields such as organic synthesis, pharmacokinetics processes, and environmental monitoring.

Immune evasion is a pivotal force shaping the evolution of viruses. Nonetheless, the extent to which virus evolution varies among populations with diverse immune backgrounds remains an unsolved mystery. Prior to the widespread SARS-CoV-2 infections in December 2022 and January 2023, the Chinese population possessed a markedly distinct (less potent) immune background due to its low infection rate, compared to countries experiencing multiple infection waves, presenting an unprecedented opportunity to investigate how the virus has evolved under different immune contexts. We compared the mutation spectrum and functional potential of the newly derived mutations that occurred in BA.5.2.48, BF.7.14 and BA.5.2.49-variants prevalent in China-with their counterparts in other countries. We found that the emerging mutations in the receptor-binding-domain region in these lineages were more widely dispersed and evenly distributed across different epitopes. These mutations led to a higher angiotensin-converting enzyme 2 (ACE2) binding affinity and reduced potential for immune evasion compared to their counterparts in other countries. These findings suggest a milder immune pressure and less evident immune imprinting within the Chinese population. Despite the emergence of numerous immune-evading variants in China, none of them outcompeted the original strain until the arrival of the XBB variant, which had stronger immune evasion and subsequently outcompeted all circulating variants. Our findings demonstrated that the continuously changing immune background led to varying evolutionary pressures on SARS-CoV-2. Thus, in addition to viral genome surveillance, immune background surveillance is also imperative for predicting forthcoming mutations and understanding how these variants spread in the population.

The gut microbiota undergoes substantial changes in COVID-19 patients; yet, the utility of these alterations as prognostic biomarkers at the time of hospital admission, and its correlation with immunological and hematological parameters, remains unclear. The objective of this study is to investigate the gut microbiota's dynamic change in critically ill patients with COVID-19 and evaluate its predictive capability for clinical outcomes alongside immunological and hematological parameters. In this study, anal swabs were consecutively collected from 192 COVID-19 patients (583 samples) upon hospital admission for metagenome sequencing. Simultaneously, blood samples were obtained to measure the concentrations of 27 cytokines and chemokines, along with hematological and biochemical indicators. Our findings indicate a significant correlation between the composition and dynamics of gut microbiota with disease severity and mortality in COVID-19 patients. Recovered patients exhibited a higher abundance of Veillonella and denser interactions among gut commensal bacteria compared to deceased patients. Furthermore, the abundance of gut commensal bacteria exhibited a negative correlation with the concentration of proinflammatory cytokines and organ damage markers. The gut microbiota upon admission showed moderate prognostic prediction ability with an AUC of 0.78, which was less effective compared to predictions based on immunological and hematological parameters (AUC 0.80 and 0.88, respectively). Noteworthy, the integration of these three datasets yielded a higher predictive accuracy (AUC 0.93). Our findings suggest the gut microbiota as an informative biomarker for COVID-19 prognosis, augmenting existing immune and hematological indicators.

Background Community-acquired pneumonia (CAP) is a common and serious condition that can be caused by a variety of pathogens. However, much remains unknown about how these pathogens interact with the lower respiratory commensals, and whether any correlation exists between the dysbiosis of the lower respiratory microbiota and disease severity and prognosis.Methods We conducted a retrospective cohort study to investigate the composition and dynamics of sputum microbiota in patients diagnosed with CAP. In total, 917 sputum specimens were collected consecutively from 350 CAP inpatients enrolled in six hospitals following admission. The V3-V4 region of the 16 S rRNA gene was then sequenced.Results The sputum microbiota in 71% of the samples were predominately composed of respiratory commensals. Conversely, 15% of the samples demonstrated dominance by five opportunistic pathogens. Additionally, 5% of the samples exhibited sterility, resembling the composition of negative controls. Compared to non-severe CAP patients, severe cases exhibited a more disrupted sputum microbiota, characterized by the highly dominant presence of potential pathogens, greater deviation from a healthy state, more significant alterations during hospitalization, and sparser bacterial interactions. The sputum microbiota on admission demonstrated a moderate prediction of disease severity (AUC = 0.74). Furthermore, different pathogenic infections were associated with specific microbiota alterations. Acinetobacter and Pseudomonas were more abundant in influenza A infections, with Acinetobacter was also enriched in Klebsiella pneumoniae infections.Conclusion Collectively, our study demonstrated that pneumonia may not consistently correlate with severe dysbiosis of the respiratory microbiota. Instead, the degree of microbiota dysbiosis was correlated with disease severity in CAP patients.

MOTIVATION:Intra-host variants refer to genetic variations or mutations that occur within an individual host organism. These variants are typically studied in the context of viruses, bacteria, or other pathogens to understand the evolution of pathogens. Moreover, intra-host variants are also explored in the field of tumor biology and mitochondrial biology to characterize somatic mutations and inherited heteroplasmic mutations. Intra-host variants can involve long insertions, deletions, and combinations of different mutation types, which poses challenges in their identification. The performance of current methods in detecting of complex intra-host variants is unknown. RESULTS:First, we simulated a dataset comprising 10 samples with 1869 intra-host variants involving various mutation patterns and benchmarked current variant detection software. The results indicated that though current software can detect most variants with F1-scores between 0.76 and 0.97, their performance in detecting long indels and low frequency variants was limited. Thus, we developed a new software, PySNV, for the detection of complex intra-host variations. On the simulated dataset, PySNV successfully detected 1863 variant cases (F1-score: 0.99) and exhibited the highest Pearson correlation coefficient (PCC: 0.99) to the ground truth in predicting variant frequencies. The results demonstrated that PySNV delivered promising performance even for long indels and low frequency variants, while maintaining computational speed comparable to other methods. Finally, we tested its performance on SARS-CoV-2 replicate sequencing data and found that it reported 21% more variants compared to LoFreq, the best-performing benchmarked software, while showing higher consistency (62% over 54%) within replicates. The discrepancies mostly exist in low-depth regions and low frequency variants. AVAILABILITY AND IMPLEMENTATION:https://github.com/bnuLyndon/PySNV/.