Search

Cold seeps harbor abundant and diverse microbes that represent a tremendous potential for biological applications and also have a significant influence on biogeochemical cycles. Though recent metagenomic studies have expanded our understanding of the microbial community and function of seep microorganisms, the knowledge of diversity and genetic repertoire of global seep microbes is lacking. Here, we collected a compilation of 165 metagenomic data from 16 cold seep sites across the globe to construct comprehensive gene and genome catalogs. The non-redundant gene catalog was comprised of 147 million genes (clustered at 95% amino acid identity), and 35.72% of them could not be assigned to a function with the currently available databases. A total of 3,164 species-level representative metagenome-assembled genomes (MAGs) are obtained, most of which (94.31%) belong to novel species. Of them, 81 ANME species are identified covering all subclades except ANME-2d, and 23 syntrophic SRB species spanning Seep-SRB1a Seep-SRB1g, and Seep-SRB2 clades. The non-redundant gene and MAGs catalogs are a valuable resource that enables expanded knowledge of the structure and functions of cold seep microbiomes.

Deep sea cold seep sediments have been discovered to harbor novel, abundant, and diverse bacterial and archaeal viruses. However, little is known about viral genetic features and evolutionary patterns in these environments. Here, we examined the evolutionary ecology of viruses across active and extinct seep stages in the area of Haima cold seeps in the South China Sea. Diverse antiviral defense systems in 487 microbial genomes spanning 43 families inform the dynamics of host-virus interactions. Accordingly, a total of 338 viral operational taxonomic units are identified and linked to 36 bacterial and archaeal phyla. Cold seep viruses are predicted to harbor diverse adaptive strategies to persist in this environment, including counter-defense systems, reverse transcriptases, auxiliary metabolic genes, and alternative genetic code assignments. Extremely low nucleotide diversity is observed in cold seep viral populations, being influenced by factors including microbial host, sediment depth and cold seep stage. Most cold seep viral genes are under strong purifying selection with trajectories that differ depending on whether cold seeps are active or extinct. This work sheds light on the understanding of environmental adaptation mechanisms and evolutionary patterns of viruses in the sub-seafloor biosphere.

Anaerobic oxidation of methane (AOM) coupled with reduction of metal oxides is supposed to be a globally important bioprocess in marine sediments. However, the responsible microorganisms and their contributions to methane budget are not clear in deep sea cold seep sediments. Here, we combined geochemistry, muti-omics and numerical modeling to study metal-dependent AOM in methanic cold seep sediments in the northern continental slope of the South China Sea. Geochemical data based on methane concentrations, carbon stable isotope, solid-phase sediment analysis and pore water measurements indicate the occurrence of anaerobic methane oxidation coupled to metal oxides reduction in the methanic zone. The 16S rRNA gene amplicons and transcripts, along with metagenomic and metatranscriptomic data suggest that diverse ANME groups actively mediated methane oxidation in the methanic zone either independently or in syntrophy with e.g. ETH-SRB1 as potential metal reducers. Modeling results suggest that the estimated rates of methane consumption via Fe-AOM and Mn-AOM were both 0.3 μmol cm-2yr-1, which account for ∼3% of total CH4removal in sediments. Overall, our results highlight metal-driven anaerobic oxidation of methane as an important methane sink in methanic cold seep sediments.

Mercury (Hg) is an important element in seafloor cold seeps that might govern methane emission. However, so far, the knowledge of biogeochemical Hg cycle in it remains poorly understood. In this study, Hg geochemical characteristics and microorganisms involved in Hg biogeochemical cycling were examined in three (active, inactive seep vs reference) different types of sediments sampled from the Haima cold seep in the South China Sea. Sediments in the active seep area were significantly enriched in mercury and methylmercury (MeHg) compared to the reference. Accordingly, abundant genes related to Hg methylation (hgcAB), demethylation (merB) and reduction (merA) were detected in the active seep sediments, phylogenetically associated with various bacterial and archaeal linages (e.g. Desulfobacterota, Gammaproteobacteria and Halobacteriota). Hg odd-mass number isotopes (Δ199Hg and Δ201Hg) pointed to their source from the upper ocean and the occurrence of abiotic dark oxidation. The δ202Hg values indicate Hg mass fractionation, migration and transformation in the active seep sediments. These geochemical and microbial data highlight active Hg biogeochemical cycles in seafloor cold seeps, functioning as important Hg-sinks and MeHg sources in the deep ocean.

Cold seeps, where cold hydrocarbon-rich fluid escapes from the seafloor, show strong enrichment of toxic metalloid arsenic (As). The toxicity and mobility of As can be greatly altered by microbial processes that play an important role in global As biogeochemical cycling. However, a global overview of genes and microbes involved in As transformation at seeps remains to be fully unveiled. Using 87 sediment metagenomes and 33 metatranscriptomes derived from 13 globally distributed cold seeps, we show that As detoxification genes (arsM, arsP, arsC1/arsC2, acr3) were prevalent at seeps and more phylogenetically diverse than previously expected. Asgardarchaeota and a variety of unidentified bacterial phyla (e.g. 4484-113, AABM5-125-24 and RBG-13-66-14) may also function as the key players in As transformation. The abundances of As cycling genes and the compositions of As-associated microbiome shifted across different sediment depths or types of cold seep. The energy-conserving arsenate reduction or arsenite oxidation could impact biogeochemical cycling of carbon and nitrogen, via supporting carbon fixation, hydrocarbon degradation and nitrogen fixation. Overall, this study provides a comprehensive overview of As cycling genes and microbes at As-enriched cold seeps, laying a solid foundation for further studies of As cycling in deep sea microbiome at the enzymatic and processual levels.

In marine ecosystems, viruses exert control on the composition and metabolism of microbial communities, thus influencing overall biogeochemical cycling. Deep sea sediments associated with cold seeps are known to host taxonomically diverse microbial communities, but little is known about viruses infecting these microorganisms. Here, we probed metagenomes from seven geographically diverse cold seeps across global oceans, to assess viral diversity, virus-host interaction, and virus-encoded auxiliary metabolic genes (AMGs). Gene-sharing network comparisons with viruses inhabiting other ecosystems reveal that cold seep sediments harbour considerable unexplored viral diversity. Most cold seep viruses display high degrees of endemism with seep fluid flux being one of the main drivers of viral community composition. In silico predictions linked 14.2% of the viruses to microbial host populations, with many belonging to poorly understood candidate bacterial and archaeal phyla. Lysis was predicted to be a predominant viral lifestyle based on lineage-specific virus/host abundance ratios. Metabolic predictions of prokaryotic host genomes and viral AMGs suggest that viruses influence microbial hydrocarbon biodegradation at cold seeps, as well as other carbon, sulfur and nitrogen cycling via virus-induced mortality and/or metabolic augmentation. Overall, these findings reveal the global diversity and biogeography of cold seep viruses and indicate how viruses may manipulate seep microbial ecology and biogeochemistry.

As an emerging and promising technology, Time Sensitive Networking (TSN) can be widely used in many real-time systems such as Industrial Internet of Things (IIoT) and Cyber Physical System (CPS). TSN, while ensuring the bounded latency and jitter, exhibits the disadvantage of not being able to efficiently use the bandwidth resources in the guard band. In this paper, we propose an algorithm family named Packet-size Aware Shaping (PAS), which is inspired by abstracting the problem of utilizing the guard band to a classic Precedence-Constrained Knapsack Problem (PCKP). PAS works with the existing TSN standards, having achieved the goal of guaranteeing the end-to-end latency for scheduled time-sensitive applications while fully utilizing the available bandwidth in the guard band for others. Furthermore, we have proposed and implemented several hardware designs for both the current standard TSN scheduler and the programmable one. The simulation results show that the PAS family can achieve satisfying performance in maximizing the resource utilization in the guard band. The synthesis results on Xilinx Vivado show that our proposed Multi-group Push-In-First-Out (MPIFO) scheduler can achieve 100 Mpps scheduling rate for 1024 scheduling items, which is fast enough to support the high-speed TSN.

Sporadic occurrences and outbreaks of hand, foot, and mouth disease (HFMD) caused by Coxsackievirus A2 (CVA2) have frequently reported worldwide recently, which pose a great challenge to public health. Epidemiological studies have suggested that the main cause of death in critical patients is pulmonary edema. However, the pathogenesis of this underlying comorbidity remains unclear. In this study, we utilized the 5-day-old BALB/c mouse model of lethal CVA2 infection to evaluate lung damage. We found that the permeability of lung microvascular was significantly increased after CVA2 infection. We also observed the direct infection and apoptosis of lung endothelial cells as well as the destruction of tight junctions between endothelial cells. CVA2 infection led to the degradation of tight junction proteins (e.g., ZO-1, claudin-5, and occludin). The gene transcription levels of von Willebrand factor (vWF), endothelin (ET), thrombomodulin (THBD), granular membrane protein 140 (GMP140), and intercellular cell adhesion molecule-1 (ICAM-1) related to endothelial dysfunction were all significantly increased. Additionally, CVA2 infection induced the increased expression of inflammatory cytokines (IL-6, IL-1β, and MCP-1) and the activation of p38 mitogen-activated protein kinase (MAPK). In conclusion, the disruption of the endothelial barrier contributes to acute lung injury induced by CVA2 infection, targeting p38-MAPK signaling may provide a therapeutic approach for pulmonary edema in critical infections of HFMD.

Sporadic occurrences and outbreaks of hand, foot, and mouth disease (HFMD) caused by Coxsackievirus A2 (CVA2) have frequently reported worldwide recently, which pose a great challenge to public health. Epidemiological studies have suggested that the main cause of death in critical patients is pulmonary edema. However, the pathogenesis of this underlying comorbidity remains unclear. In this study, we utilized the 5-day-old BALB/c mouse model of lethal CVA2 infection to evaluate lung damage. We found that the permeability of lung microvascular was significantly increased after CVA2 infection. We also observed the direct infection and apoptosis of lung endothelial cells as well as the destruction of tight junctions between endothelial cells. CVA2 infection led to the degradation of tight junction proteins (e.g., ZO-1, claudin-5, and occludin). The gene transcription levels of von Willebrand factor (vWF), endothelin (ET), thrombomodulin (THBD), granular membrane protein 140 (GMP140), and intercellular cell adhesion molecule-1 (ICAM-1) related to endothelial dysfunction were all significantly increased. Additionally, CVA2 infection induced the increased expression of inflammatory cytokines (IL-6, IL-1β, and MCP-1) and the activation of p38 mitogen-activated protein kinase (MAPK). In conclusion, the disruption of the endothelial barrier contributes to acute lung injury induced by CVA2 infection; targeting p38-MAPK signaling may provide a therapeutic approach for pulmonary edema in critical infections of HFMD.

TCAM is widely used for flow table lookup in Software-Defined Networking (SDN) switches for datacenter and enterprise networks. While its lookup throughput is unparalleled, TCAM updating, particularly for new rule insertions, can impair the overall system performance. A rule insertion entails two steps: 1) Computing the rule moving operations; and 2) Interrupting the TCAM lookups to apply the operations. In previous work, the performance gain on one step is always at the expense of the performance loss on the other. However, update throughput and latency depend on both. In this paper, we present a faster and more balanced TCAM update scheme, which not only achieves the shortest interrupt time so far but also significantly reduces the computation time. By using a novel sequential stack, FastUp reduces the time and space complexity of the state-of-the-art schemes from $O(m^{2})$ and $O(m)$ to $O(m\log h)$ and $O(h)$ , respectively, where $h . Evaluations show that FastUp shortens the computation time and the interrupt time by $100\times$ and $1.6\times$ , respectively, which is equivalent to update delay ${15\times}$ reduction and $\mathbf{10\times}$ update throughput gain against the state-of-the-art schemes. Moreover, we debunk a common mistake and show the dynamic programming based algorithm cannot be used to solve the reorder problem, and instead we use a bidirectional rule moving method to address the problem. In addition, we propose a practical method to find the theoretical lower bound of interrupt time in relatively large TCAM, which can be used to evaluate the optimality degree of TCAM update schemes. Evaluations show that FastUp achieves 90 % optimality.

The network link speed is growing at an ever-increasing rate, which requires all network functions on routers/switches to keep pace. Bloom filter is a widely-used membership check data structure in networking applications. Correspondingly, it also faces the urgent demand of improving the performance in membership check speed. To this end, this paper proposes a new Bloom filter variant called Ultra-Fast Bloom Filters (UFBF), by leveraging the Single Instruction Multiple Data (SIMD) techniques. We make three improvements for UFBF to accelerate the membership check speed. First, we develop a novel hash computation algorithm which can compute multiple hash functions in parallel with the use of SIMD instructions. Second, we elaborate a Bloom filter’s bit-test process from sequential to parallel, enabling more bit-tests per unit time. Third, we improve the cache efficiency of membership check by encoding an element’s information to a small block so that it can fit into a cache-line. We further generalize UFBF, called c-UFBF, to make UFBF supporting large number of hash functions. Both theoretical analysis and extensive evaluations show that the UFBF greatly outperforms the state-of-the-art Bloom filter variants on membership check speed.

The statistical power of genome-wide association studies (GWASs) is affected by the effective sample size. However, the privacy and security concerns associated with individual-level genotype data pose great challenges for cross-institutional cooperation. The full-process cryptographic solutions are in demand but have not been covered, especially the essential principal-component analysis (PCA). Here, we present TrustGWAS, a complete solution for secure, large-scale GWAS, recapitulating gold standard results against PLINK without compromising privacy and supporting basic PLINK steps including quality control, linkage disequilibrium pruning, PCA, chi-square test, Cochran-Armitage trend test, covariate-supported logistic regression and linear regression, and their sequential combinations. TrustGWAS leverages pseudorandom number perturbations for PCA and multiparty scheme of multi-key homomorphic encryption for all other modules. TrustGWAS can evaluate 100,000 individuals with 1 million variants and complete QC-LD-PCA-regression workflow within 50 h. We further successfully discover gene loci associated with fasting blood glucose, consistent with the findings of the ChinaMAP project.

Vehicle to Vehicle (V2V) communication opens a new way to make vehicles directly communicate with each other, providing faster responses for time-sensitive tasks than cellular networks. Effective V2V routing protocols are essential yet challenging, as the high dynamic road environment makes communication easy to break. Many prediction methods proposed in the existing protocols to address this issue are either flawed or have a poor effect. In this paper, to cope with the two aspects of the problems that cause communication interrupt, i.e., link breaks and route quality degradation, we design an acceleration-based trajectory prediction algorithm to estimate the link lifetime, and a machine learning model to predict route quality. Based on the prediction algorithms, we propose PQR, a Prediction-supported Quality-aware Routing protocol, which can proactively switch to a better route before the current link breaks or the route quality degrades. Especially, considering the limitations of the current routing protocols, we elaborate a new hybrid routing protocol that integrates the topology-based method and location-based method to achieve instant communication. Simulation results show that PQR outperforms the existing protocols in Packet Delivery Ratio (PDR), Roundtrip Time (RTT), and Normalized Routing Overhead (NRO). Specifically, we have also implemented a vehicular testbed to demonstrate PQR’s real-world performance, and results show that PQR achieves almost no packet loss with latency less than 10ms during route handoff for topology change.

Offloading the 3D object detection from autonomous vehicles to MEC is appealing because of the gains on quality, latency, and energy. However, detection requests lead to repetitive computations since the multitudinous requests share approximate detection results. It is crucial to reduce such fuzzy redundancy by reusing the previous results. A key challenge is that the requests mapping to the reusable result are only similar but not identical. An efficient method for similarity matching is needed to justify the use case. To this end, by taking advantage of TCAM’s ap-proximate matching capability and NMC’s computing efficiency, we design SODA, a first-of-its-kind hardware accelerator which sits in the mobile base stations between autonomous vehicles and MEC servers. We design efficient feature encoding and partition algorithms for SODA to ensure the quality of the similarity matching and result reuse. Our evaluation shows that SODA significantly improves the system performance and the detection results exceed the accuracy requirements on the subject matter, qualifying SODA as a practical domain-specific solution.

Rule update in TCAM has long been identified as a key technical challenge due to the rule order constraint. Existing algorithms take each rule update as an independent task. However, emerging applications produce batch rule update requests. Processing the updates individually causes high aggregated cost which can strain the processor and/or incur excessive TCAM lookup interrupts. This paper presents the first true batch update algorithm, ABUT. Unlike the other alleged batch update algorithms, ABUT collectively evaluates and optimizes the TCAM placement for whole batches throughout. By applying the topology grouping and maintaining the group order invariance in TCAM, ABUT achieves substantial computing time reduction yet still yields the best-in-class placement cost. Our evaluations show that ABUT is ideal for low-latency and high-throughput batch TCAM updates in modern high-performance switches.

The seafloor sulfide structures of inactive vents are known to host abundant and diverse microorganisms potentially supported by mineralogy of sulfides. However, little is known about the diversity and distribution of microbial functions. Here, we used genome-resolved metagenomics to predict microbial metabolic functions and the contribution of horizontal gene transfer to the functionality of microorganisms inhabiting several hydrothermally inactive seafloor deposits among globally distributed deep-sea vent fields. Despite of geographically distant vent fields, similar microbial community patterns were observed with the dominance of Gammaproteobacteria, Bacteroidota and previously overlooked Candidatus Patescibacteria. Metabolically flexible Gammaproteobacteria are major potential primary producers utilizing mainly sulfur, iron and hydrogen as electron donors coupled with oxygen and nitrate respiration for chemolithoautotrophic growth. In addition to heterotrophic microorganisms like free-living Bacteroidota, Ca. Patescibacteria potentially perform fermentative recycling of organic carbon. Finally, we provided evidence that many functional genes that are central to energy metabolism have been laterally transferred among members within the community and largely within the same class. Taken together, these findings shed light on microbial ecology and evolution in inactive seafloor sulfide deposits after the cessation of hydrothermal activities.