Hypoxia causes trophoblast cell ferroptosis to induce miscarriage through lnc-HZ06/HIF1α-SUMO/NCOA4 axis.

Defects of human trophoblast cells may induce miscarriage (abnormal early embryo loss), which is generally regulated by lncRNAs. Ferroptosis is a newly identified iron-dependent programmed cell death. Hypoxia is an important and unavoidable feature in mammalian cells. However, whether hypoxia might induce trophoblast cell ferroptosis and then induce miscarriage, as well as regulated by a lncRNA, was completely unknown. In this work, we discovered at the first time that hypoxia could result in ferroptosis of human trophoblast cells and then induce miscarriage. We also identified a novel lncRNA (lnc-HZ06) that simultaneously regulated hypoxia (indicated by HIF1α protein), ferroptosis, and miscarriage. In mechanism, HIF1α-SUMO, instead of HIF1α itself, primarily acted as a transcription factor to promote the transcription of NCOA4 (ferroptosis indicator) in hypoxic trophoblast cells. Lnc-HZ06 promoted the SUMOylation of HIF1α by suppressing SENP1-mediated deSUMOylation. HIF1α-SUMO also acted as a transcription factor to promote lnc-HZ06 transcription. Thus, both lnc-HZ06 and HIF1α-SUMO formed a positive auto-regulatory feedback loop. This loop was up-regulated in hypoxic trophoblast cells, in RM villous tissues, and in placental tissues of hypoxia-treated mice, which further induced ferroptosis and miscarriage by up-regulating HIF1α-SUMO-mediated NCOA4 transcription. Furthermore, knockdown of either murine lnc-hz06 or Ncoa4 could efficiently suppress ferroptosis and alleviate miscarriage in hypoxic mouse model. Taken together, this study provided new insights in understanding the regulatory roles of lnc-HZ06/HIF1α-SUMO/NCOA4 axis among hypoxia, ferroptosis, and miscarriage, and also offered an effective approach for treatment against miscarriage.

Physiological Response of Spotted Seabass (Lateolabrax maculatus) to Different Dietary Available Phosphorus Levels and Water Temperature: Changes in Growth, Lipid Metabolism, Antioxidant Status and Intestinal Microbiota.

A 10-week growth experiment was conducted to assess the physiological response of spotted seabass (Lateolabrax maculatus) raised at moderate (27 °C) and high temperatures (33 °C) to different dietary available phosphorus (P) levels. Five diets with available P levels of 0.35, 0.55, 0.71, 0.82 and 0.92% were formulated, respectively. A water temperature of 33 °C significantly decreased growth performance and feed utilization, and increased oxidative stress and lipid deposition of spotted seabass compared with 27 °C. A second-order polynomial regression analysis based on weight gain (WG) showed that the available P requirement of spotted seabass raised at 27 °C and 33 °C was 0.72% and 0.78%, respectively. The addition of 0.71-0.82% P to the diet improved the growth performance, feed utilization, and antioxidant capacity of spotted seabass and alleviated the excessive lipid deposition compared with the low-P diet (0.35% P). Moreover, the addition of 0.71-0.92% P to diets increased the diversity of intestinal microbiota and the relative abundance of Lactococcus lactis and decreased the relative abundance of Plesiomonas compared with the low-P diet. Thus, dietary supplementation with 0.71-0.82% P improved the growth performance, antioxidant capacity and microbial composition of spotted seabass, and alleviated the disturbance of lipid metabolism caused by high temperature or low-P diet.

Nano-Impact Electrochemical Biosensing Based on a CRISPR-Responsive DNA Hydrogel.

Nano-impact electrochemistry (NIE) enables simple, rapid, and high-throughput biocoupling and biomolecular recognition. However, the low effective collision frequency limits the sensitivity. In this study, we propose a novel NIE sensing strategy amplified by the CRISPR-responsive DNA hydrogel and cascade DNA assembly. By controlling the phase transition of DNA hydrogel and the self-electrolysis of silver nanoparticles, we can obtain significant electrochemical responses. The whole process includes target miRNA-induced strand displacement amplification, catalytic hairpin assembly, and CRISPR/Cas trans-cutting. Thus, ultrahigh sensitivity is promised. This NIE biosensing strategy achieves a limit of detection as low as 4.21 aM for miR-141 and demonstrates a high specificity for practical applications. It may have wide applicability in nucleic acid sensing and shows great potential in disease diagnosis.

Combining multi-omics analysis to identify host-targeted targets for the control of Brucella infection.

Human infections caused by Brucella (called brucellosis) are among the most common zoonoses worldwide with an estimated 500,000 cases each year. Since chronic Brucella infections are extremely difficult to treat, there is an urgent need for more effective therapeutics. As a facultative intracellular bacterium, Brucella is strictly parasitic in the host cell. Here, we performed proteomic and transcriptomic and metabolomic analyses on Brucella infected patients, mice and cells that provided an extensive "map" of physiological changes in brucellosis patients and characterized the metabolic pathways essential to the response to infection, as well as the associated cellular response and molecular mechanisms. This is the first report utilizing multi-omics analysis to investigate the global response of proteins and metabolites associated with Brucella infection, and the data can provide a comprehensive insight to understand the mechanism of Brucella infection. We demonstrated that Brucella increased nucleotide synthesis in the host, consistent with increased biomass requirement. We also identified IMPDH2, a key regulatory complex that controls nucleotide synthesis during Brucella infection. Pharmacological targeting of IMPDH2, the rate-limiting enzyme in guanine nucleotide biosynthesis, efficiently inhibits B. abortus growth both in vitro and in vivo. Through screening a library of natural products, we identified oxymatrine, an alkaloid obtained primarily from Sophora roots, is a novel and selective IMPDH2 inhibitor. In further in vitro bacterial inhibition assays, oxymatrine effectively inhibited the growth of B. abortus, which was impaired by exogenous supplementation of guanosine, a salvage pathway of purine nucleotides. This moderately potent, structurally novel compound may provide clues for further design and development of efficient IMPDH2 inhibitors and also demonstrates the potential of natural compounds from plants against Brucella.

Bio-Inspired Electrochemical Detection of Nitric Oxide Promoted by Coordinating the Histamine-Iron Phthalocyanine Catalytic Center on Microelectrode.

Biomimetic structures to fabricate bioelectronic interfaces that allow sensors to electrically communicate with electrodes have potential applications in the development of biosensors. Herein, inspired by the structure feature of nitric oxide (NO) sensory protein, we constructed a biomimetically catalytic center, the histamine coordinated iron phthalocyanine (FePc), for efficient and sensitive detection of NO. In specific, NO is recognized by axial tethered FePc, and the oxidative signal of NO on FePc is converted into output signal through electrocatalytic oxidation. Based on the fabricated catalytic structure on the carbon fiber electrode, on one hand, the macrocyclic π system of FePc enabled a rapid redox process, which facilitates electron transfer, thereby greatly improving sensitivity. On the other hand, by coordination with histamine on the electrode surface, FePc can enhance the electrochemical oxidation activity toward NO and promote catalytic detection, which have been revealed by electrochemical characterizations and density functional theory theoretical calculations. The designed electrochemical microsensor exhibits a low limit of detection (0.03 nM) and shows a wide detection range (0.1 nM-2 µM). In addition, the electrochemical microsensor has been successfully used for real-time monitoring of NO release by live cells. So, this work shows a new strategy for the design of bio-inspired electrochemical microsensors that may provide a potential analytical tool for tracing biological signal molecules with enzyme-free biomimetically catalytic centers.

Diversity and ecological footprint of Global Ocean RNA viruses.

DNA viruses are increasingly recognized as influencing marine microbes and microbe-mediated biogeochemical cycling. However, little is known about global marine RNA virus diversity, ecology, and ecosystem roles. In this study, we uncover patterns and predictors of marine RNA virus community- and "species"-level diversity and contextualize their ecological impacts from pole to pole. Our analyses revealed four ecological zones, latitudinal and depth diversity patterns, and environmental correlates for RNA viruses. Our findings only partially parallel those of cosampled plankton and show unexpectedly high polar ecological interactions. The influence of RNA viruses on ecosystems appears to be large, as predicted hosts are ecologically important. Moreover, the occurrence of auxiliary metabolic genes indicates that RNA viruses cause reprogramming of diverse host metabolisms, including photosynthesis and carbon cycling, and that RNA virus abundances predict ocean carbon export.

The International Virus Bioinformatics Meeting 2022.

The International Virus Bioinformatics Meeting 2022 took place online, on 23-25 March 2022, and has attracted about 380 participants from all over the world. The goal of the meeting was to provide a meaningful and interactive scientific environment to promote discussion and collaboration and to inspire and suggest new research directions and questions. The participants created a highly interactive scientific environment even without physical face-to-face interactions. This meeting is a focal point to gain an insight into the state-of-the-art of the virus bioinformatics research landscape and to interact with researchers in the forefront as well as aspiring young scientists. The meeting featured eight invited and 18 contributed talks in eight sessions on three days, as well as 52 posters, which were presented during three virtual poster sessions. The main topics were: SARS-CoV-2, viral emergence and surveillance, virus-host interactions, viral sequence analysis, virus identification and annotation, phages, and viral diversity. This report summarizes the main research findings and highlights presented at the meeting.

Cryptic and abundant marine viruses at the evolutionary origins of Earth's RNA virome.

Whereas DNA viruses are known to be abundant, diverse, and commonly key ecosystem players, RNA viruses are insufficiently studied outside disease settings. In this study, we analyzed ≈28 terabases of Global Ocean RNA sequences to expand Earth's RNA virus catalogs and their taxonomy, investigate their evolutionary origins, and assess their marine biogeography from pole to pole. Using new approaches to optimize discovery and classification, we identified RNA viruses that necessitate substantive revisions of taxonomy (doubling phyla and adding >50% new classes) and evolutionary understanding. "Species"-rank abundance determination revealed that viruses of the new phyla "Taraviricota," a missing link in early RNA virus evolution, and "Arctiviricota" are widespread and dominant in the oceans. These efforts provide foundational knowledge critical to integrating RNA viruses into ecological and epidemiological models.

Prevalence of Latent Tuberculosis Infection Among Healthy Young Children and Adolescents and a Two-step Approach for the Diagnosis of Tuberculosis Infection in Chengdu, China.

BACKGROUND: China has a high burden of tuberculosis and latent tuberculosis infection (LTBI). The aim of this study was to estimate the prevalence of LTBI among healthy young children and adolescents and test a 2-step approach to explore the threshold for the diagnosis of tuberculosis infection in Chengdu, China. METHODS: Healthy preschool children and school-going children in Chengdu, Sichuan Province, were screened for LTBI using the tuberculin skin test (TST). Preschool children with TST ≥ 5 mm also underwent interferon-γ release assay (IGRA) to explore the threshold of this 2-step approach. RESULTS: In total, 5667 healthy young children and adolescents completed TST test between July 2020 and January 2021 and were included in the present analysis. The age of the participants ranged from 2.4 to 18 years (median 7.25 ± 4.514 years), of which 2093 (36.9%) were younger than 5 years. The overall prevalence of LTBI was 6.37% and 6.64% in children younger than 5 years old. Fourteen of the 341 preschool children with TST ≥5 mm were interferon-γ release assay positive, of which 4 showed a TST result of 5-10 mm, and 6 preschool children received preventive treatment for LTBI. CONCLUSIONS: Healthy young children and adolescents should also be considered as important target populations for LTBI screening. TST can be recommended for first-line screening as part of a 2-step approach for LTBI screening using a positive threshold of 5 mm.

Direct acupuncture of nitric oxide by an electrochemical microsensor with high time-space resolution.

Measurement of signal molecule is critically important for understanding living systems. Nitric oxide (NO) is a key redox signal molecule that shows diverse roles in virtually all life forms. However, probing into NO's activities is challenging as NO has restricted lifetime (<10 s) and limited diffusion distance (usually <200 µm). So, for the direct acupuncture of NO within the time-space resolution, an electrochemical microsensor has been designed and fabricated in this work. Fabrication of the microsensor is achieved by (1) selective assembly of an electrocatalytic transducer, (2) attaching the transducer on carbon fiber electrode, and (3) covered it with a screen layer to reduce signal interference. The fabricated microsensor exhibits high sensitivity (LOD, 13.5 pM), wide detection range (100 pM-5 µM), and good selectivity. Moreover, studies have revealed that the availability of the sensor for efficient detection of NO is due to the formation of a specific DNA/porphyrin hybrid structure that has synergetic effects on NO electrocatalysis. Therefore, NO release by cells and tissues can be directly and precisely traced, in which we have obtained the release pattern of NO by different cancer cell lines, and have known its dynamics in tumor microenvironment. The fabricated electrocatalytic microsensor may provide a unique and useful tool for the direct assay of NO with high time-space resolution, which promisingly gives a technical solution for the bioassay of NO in living systems.

[A review of brain-like spiking neural network and its neuromorphic chip research].

Under the current situation of the rapid development of brain-like artificial intelligence and the increasingly complex electromagnetic environment, the most bionic and anti-interference spiking neural network has shown great potential in computing speed, real-time information processing, and spatiotemporal data processing. Spiking neural network is the core part of brain-like artificial intelligence, which realizes brain-like computing by simulating the structure of biological neural network and the way of information transmission. This article first summarizes the advantages and disadvantages of the five models, and analyzes the characteristics of several network topologies. Then, it summarizes the spiking neural network algorithms. The unsupervised learning based on spike timing dependent plasticity (STDP) rules and four types of supervised learning algorithms are analyzed. Finally, the research on brain-like neuromorphic chips at home and abroad are reviewed. This paper aims to provide learning ideas and research directions for new colleagues in the field of spiking neural network.

Expanding standards in viromics: in silico evaluation of dsDNA viral genome identification, classification, and auxiliary metabolic gene curation.

BACKGROUND: Viruses influence global patterns of microbial diversity and nutrient cycles. Though viral metagenomics (viromics), specifically targeting dsDNA viruses, has been critical for revealing viral roles across diverse ecosystems, its analyses differ in many ways from those used for microbes. To date, viromics benchmarking has covered read pre-processing, assembly, relative abundance, read mapping thresholds and diversity estimation, but other steps would benefit from benchmarking and standardization. Here we use in silico-generated datasets and an extensive literature survey to evaluate and highlight how dataset composition (i.e., viromes vs bulk metagenomes) and assembly fragmentation impact (i) viral contig identification tool, (ii) virus taxonomic classification, and (iii) identification and curation of auxiliary metabolic genes (AMGs). RESULTS: The in silico benchmarking of five commonly used virus identification tools show that gene-content-based tools consistently performed well for long (≥3 kbp) contigs, while k-mer- and blast-based tools were uniquely able to detect viruses from short (≤3 kbp) contigs. Notably, however, the performance increase of k-mer- and blast-based tools for short contigs was obtained at the cost of increased false positives (sometimes up to ∼5% for virome and ∼75% bulk samples), particularly when eukaryotic or mobile genetic element sequences were included in the test datasets. For viral classification, variously sized genome fragments were assessed using gene-sharing network analytics to quantify drop-offs in taxonomic assignments, which revealed correct assignations ranging from ∼95% (whole genomes) down to ∼80% (3 kbp sized genome fragments). A similar trend was also observed for other viral classification tools such as VPF-class, ViPTree and VIRIDIC, suggesting that caution is warranted when classifying short genome fragments and not full genomes. Finally, we highlight how fragmented assemblies can lead to erroneous identification of AMGs and outline a best-practices workflow to curate candidate AMGs in viral genomes assembled from metagenomes. CONCLUSION: Together, these benchmarking experiments and annotation guidelines should aid researchers seeking to best detect, classify, and characterize the myriad viruses 'hidden' in diverse sequence datasets.

Metagenomic analysis reveals the shared and distinct features of the soil resistome across tundra, temperate prairie, and tropical ecosystems.

BACKGROUND: Soil is an important reservoir of antibiotic resistance genes (ARGs), but their potential risk in different ecosystems as well as response to anthropogenic land use change is unknown. We used a metagenomic approach and datasets with well-characterized metadata to investigate ARG types and amounts in soil DNA of three native ecosystems: Alaskan tundra, US Midwestern prairie, and Amazon rainforest, as well as the effect of conversion of the latter two to agriculture and pasture, respectively. RESULTS: High diversity (242 ARG subtypes) and abundance (0.184-0.242 ARG copies per 16S rRNA gene copy) were observed irrespective of ecosystem, with multidrug resistance and efflux pump the dominant class and mechanism. Ten regulatory genes were identified and they accounted for 13-35% of resistome abundances in soils, among them arlR, cpxR, ompR, vanR, and vanS were dominant and observed in all studied soils. We identified 55 non-regulatory ARGs shared by all 26 soil metagenomes of the three ecosystems, which accounted for more than 81% of non-regulatory resistome abundance. Proteobacteria, Firmicutes, and Actinobacteria were primary ARG hosts, 7 of 10 most abundant ARGs were found in all of them. No significant differences in both ARG diversity and abundance were observed between native prairie soil and adjacent long-term cultivated agriculture soil. We chose 12 clinically important ARGs to evaluate at the sequence level and found them to be distinct from those in human pathogens, and when assembled they were even more dissimilar. Significant correlation was found between bacterial community structure and resistome profile, suggesting that variance in resistome profile was mainly driven by the bacterial community composition. CONCLUSIONS: Our results identify candidate background ARGs (shared in all 26 soils), classify ARG hosts, quantify resistance classes, and provide quantitative and sequence information suggestive of very low risk but also revealing resistance gene variants that might emerge in the future. Video abstract.

Upregulated lnc-HZ02 and miR-hz02 inhibited migration and invasion by downregulating the FAK/SRC/PI3K/AKT pathway in BPDE-treated trophoblast cells.

BPDE (benzo(a)pyren-7,8-dihydrodiol-9,10-epoxide), a metabolite of environmental carcinogenic BaP, weakens the migration and invasion of human villous trophoblast cells and may further induce miscarriage. However, the underlying mechanisms remain largely unknown. In this study, we identified that in trophoblast Swan 71 and HTR-8/SVneo cells, miR-hz02 upregulates the level of lnc-HZ02, which inhibits the expression of an RNA-binding protein HuR. HuR could interact with FAK mRNA and promote its mRNA stability, thus upregulating the FAK level and the FAK/SRC/PI3K/AKT pathway, and finally maintaining the normal migration and invasion of trophoblast cells. If trophoblast cells are exposed to BPDE, both miR-hz02 and lnc-HZ02 are upregulated, which reduce the level of HuR, weaken the interactions of HuR with FAK mRNA, downregulate FAK level and the FAK/SRC/PI3K/AKT pathway, and finally inhibit cell migration and invasion. This study provides a novel scientific understanding of the dysfunctions of human trophoblast cells.

Lnc-HZ01 with m6A RNA methylation inhibits human trophoblast cell proliferation and induces miscarriage by up-regulating BPDE-activated lnc-HZ01/MXD1 positive feedback loop.

Environmental BaP (benzo(a)pyrene) and its metabolite BPDE (benzo(a)pyrene-7,8-dihydrodiol-9,10-epoxide) inhibit proliferation of human villous trophoblast cells, which might further induce recurrent miscarriage (RM). However, the underlying mechanisms remain largely unknown. In this work, we identified a novel lncRNA HZ01 (lnc-HZ01) that is up-regulated in both RM tissues and BPDE-exposed trophoblast cells. Lnc-HZ01 inhibits trophoblast cell proliferation and induces miscarriage. Mechanistically, lnc-HZ01 promotes MXD1 mRNA transcription by up-regulating its transcription factor c-JUN and also enhances MXD1 protein stability by up-regulating its deubiquitin enzyme USP36. Reversely, MXD1 up-regulates lnc-HZ01 level by enhancing its RNA stability due to the increased level of m6A RNA methylation on lnc-HZ01, the first example that m6A modification regulates trophoblast cell functions. Thus, lnc-HZ01 and MXD1 comprise a positive self-feedback loop, which is up-regulated in both RM tissues and BPDE-exposed trophoblast cells. Once this loop is activated by BaP or BPDE exposure, both pathways in this loop would be up-regulated, promote EIF4E transcription, inhibit trophoblast cell proliferation, and further induce miscarriage. This work provides new clinical and scientific understanding in unexplained miscarriage.

Introduction to Environmental Harmful Factors.

In this Chapter, we systematically and comprehensively described various environmental harmful factors. They were classified into four aspects: physical factors, chemical factors, biological factors, and physiological and psychological stress factors. Their classification, modes of presence, toxicity and carcinogenicity, routes of exposure to human and toxic effects on the female reproductive health were introduced. It is expected that the exposure routes could be controlled and eliminated, and the pathogenic mechanism of environmental harmful factors should be investigated and explained to protect female reproductive health.

VirSorter2: a multi-classifier, expert-guided approach to detect diverse DNA and RNA viruses.

BACKGROUND: Viruses are a significant player in many biosphere and human ecosystems, but most signals remain "hidden" in metagenomic/metatranscriptomic sequence datasets due to the lack of universal gene markers, database representatives, and insufficiently advanced identification tools. RESULTS: Here, we introduce VirSorter2, a DNA and RNA virus identification tool that leverages genome-informed database advances across a collection of customized automatic classifiers to improve the accuracy and range of virus sequence detection. When benchmarked against genomes from both isolated and uncultivated viruses, VirSorter2 uniquely performed consistently with high accuracy (F1-score > 0.8) across viral diversity, while all other tools under-detected viruses outside of the group most represented in reference databases (i.e., those in the order Caudovirales). Among the tools evaluated, VirSorter2 was also uniquely able to minimize errors associated with atypical cellular sequences including eukaryotic genomes and plasmids. Finally, as the virosphere exploration unravels novel viral sequences, VirSorter2's modular design makes it inherently able to expand to new types of viruses via the design of new classifiers to maintain maximal sensitivity and specificity. CONCLUSION: With multi-classifier and modular design, VirSorter2 demonstrates higher overall accuracy across major viral groups and will advance our knowledge of virus evolution, diversity, and virus-microbe interaction in various ecosystems. Source code of VirSorter2 is freely available ( https://bitbucket.org/MAVERICLab/virsorter2 ), and VirSorter2 is also available both on bioconda and as an iVirus app on CyVerse ( https://de.cyverse.org/de ). Video abstract.

iVirus 2.0: Cyberinfrastructure-supported tools and data to power DNA virus ecology.

Microbes drive myriad ecosystem processes, but under strong influence from viruses. Because studying viruses in complex systems requires different tools than those for microbes, they remain underexplored. To combat this, we previously aggregated double-stranded DNA (dsDNA) virus analysis capabilities and resources into 'iVirus' on the CyVerse collaborative cyberinfrastructure. Here we substantially expand iVirus's functionality and accessibility, to iVirus 2.0, as follows. First, core iVirus apps were integrated into the Department of Energy's Systems Biology KnowledgeBase (KBase) to provide an additional analytical platform. Second, at CyVerse, 20 software tools (apps) were upgraded or added as new tools and capabilities. Third, nearly 20-fold more sequence reads were aggregated to capture new data and environments. Finally, documentation, as "live" protocols, was updated to maximize user interaction with and contribution to infrastructure development. Together, iVirus 2.0 serves as a uniquely central and accessible analytical platform for studying how viruses, particularly dsDNA viruses, impact diverse microbial ecosystems.

Impact of dichlorprop on soil microbial community structure and diversity during its enantioselective biodegradation in agricultural soils.

Enantioselective biodegradation of racemic dichlorprop in two soils was investigated in the laboratory. Chiral separation of racemic dichlorprop was achieved by using HPLC with Phenomenex Lux Amylose-2. The first-order kinetic model fitted well the dissipation data of racemic dichlorprop and its pure R- and S-enantiomers. S-dichlorprop was preferentially degraded in both soils and enantioselectivity was affected by soil pH. The half-lives (DT50) of S-dichlorprop were 8.22 days in soil A and 8.06 days in soil D, while R-dichlorprop was more persistent with DT50 of 12.93 days in soil A and 12.38 days in soil D, respectively. Dichlorprop dissipated faster in soil D with lower organic matter content. In sterilized soils, neglected dissipation was observed and enantiomer fraction values remained constant, indicating that the enantioselective degradation was mainly controlled by soil microorganisms. Soil microbial community structure and diversity was assessed by Illumina MiSeq sequencing of 16S rRNA genes from dichlorprop and no dichlorprop contaminated microcosms. Compared with controls, dichlorprop application had no significant effect on microbial community structures at phylum level, but increased bacterial diversity and dichlorprop degradation related taxa in both soils. S-dichlorprop preferential degradation might be attributed to the S-enantiomer preferred degraders in the family of Sphingomonadaceae.

Review, Evaluation, and Directions for Gene-Targeted Assembly for Ecological Analyses of Metagenomes.

Shotgun metagenomics has greatly advanced our understanding of microbial communities over the last decade. Metagenomic analyses often include assembly and genome binning, computationally daunting tasks especially for big data from complex environments such as soil and sediments. In many studies, however, only a subset of genes and pathways involved in specific functions are of interest; thus, it is not necessary to attempt global assembly. In addition, methods that target genes can be computationally more efficient and produce more accurate assembly by leveraging rich databases, especially for those genes that are of broad interest such as those involved in biogeochemical cycles, biodegradation, and antibiotic resistance or used as phylogenetic markers. Here, we review six gene-targeted assemblers with unique algorithms for extracting and/or assembling targeted genes: Xander, MegaGTA, SAT-Assembler, HMM-GRASPx, GenSeed-HMM, and MEGAN. We tested these tools using two datasets with known genomes, a synthetic community of artificial reads derived from the genomes of 17 bacteria, shotgun sequence data from a mock community with 48 bacteria and 16 archaea genomes, and a large soil shotgun metagenomic dataset. We compared assemblies of a universal single copy gene (rplB) and two N cycle genes (nifH and nirK). We measured their computational efficiency, sensitivity, specificity, and chimera rate and found Xander and MegaGTA, which both use a probabilistic graph structure to model the genes, have the best overall performance with all three datasets, although MEGAN, a reference matching assembler, had better sensitivity with synthetic and mock community members chosen from its reference collection. Also, Xander and MegaGTA are the only tools that include post-assembly scripts tuned for common molecular ecology and diversity analyses. Additionally, we provide a mathematical model for estimating the probability of assembling targeted genes in a metagenome for estimating required sequencing depth.