Host Genetic Effects Research Articles

Bacterial Assembly in the Switchgrass Rhizosphere Is Shaped by Phylogeny, Host Genotype, and Growing Site

If microbial traits are phylogenetically conserved, then variation in traits of plant hosts may influence rhizosphere microbiomes at higher taxonomic levels. To test this hypothesis and genotype-by-environment-by-microbiome (G×E×M) interactions in switchgrass (Panicum virgatum), we assessed rhizosphere bacterial composition using 128 host genotypes grown at three distinct field sites. First, we found that growing site was a substantial driver of bacterial composition, and that specific bacterial taxa correlated with differences in disease incidence and yield across environments. Second, broad-sense heritability analyses revealed that host genetic effects on rhizosphere composition were strongest at the genus level, suggesting a conserved genetic basis for shaping beneficial or pathogenic taxa. Third, we identified shared host genetic variants associated with bacterial abundance and plant metabolism, indicating possible linkages between key microbial traits and agronomic performance. These findings underscore the importance of incorporating rhizosphere microbiomes into switchgrass breeding efforts and call for further investigation of G×E×M interactions to pinpoint microbial interventions that enhance yield and disease resistance.

Sequence-based genome-wide association study reveals host genomic regions and candidate genes influencing the fecal microbiota of Holstein cows.

Sequence-based genome-wide association study reveals host genomic regions and candidate genes influencing the fecal microbiota of Holstein cows.

Increasing spatial working memory in mice with Akkermansia muciniphila

Recent research has shown the gut microbiome’s impact on memory, yet limitations hinder the identification of specific microbes linked to cognitive function. We measured spatial working memory in individual mice before and after fecal microbiota transplantation (FMT) to develop a targeted analysis that identifies memory-associated strains while minimizing host genetic effects. Transplantation of human fecal into C57BL/6 mice yielded varied outcomes: some mice showed significant improvements while others had negligible changes, indicating that these changes are due to differences in FMT colonization. Metagenomic analysis, stratified by memory performance, revealed a positive correlation between the abundance of Akkermansia muciniphila and improved memory. Moreover, administering two A. muciniphila strains, GMB 0476 and GMB 2066, to wild-type mice elevated spatial working memory via BDNF activation. Our findings indicate that specific gut microbes, particularly A. muciniphila, may modulate memory and represent potential targets for therapeutic intervention in cognitive enhancement.

SIRE 2.0: a novel method for estimating polygenic host effects underlying infectious disease transmission, and analytical expressions for prediction accuracies

BackgroundGenetic selection of individuals that are less susceptible to infection, less infectious once infected, and recover faster, offers an effective and long-lasting solution to reduce the incidence and impact of infectious diseases in farmed animals. However, computational methods for simultaneously estimating genetic parameters for host susceptibility, infectivity and recoverability from real-word data have been lacking. Our previously developed methodology and software tool SIRE 1.0 (Susceptibility, Infectivity and Recoverability Estimator) allows estimation of host genetic effects of a single nucleotide polymorphism (SNP), or other fixed effects (e.g. breed, vaccination status), for these three host traits using individual disease data typically available from field studies and challenge experiments. SIRE 1.0, however, lacks the capability to estimate genetic parameters for these traits in the likely case of underlying polygenic control.ResultsThis paper introduces novel Bayesian methodology and a new software tool SIRE 2.0 for estimating polygenic contributions (i.e. variance components and additive genetic effects) for host susceptibility, infectivity and recoverability from temporal epidemic data, assuming that pedigree or genomic relationships are known. Analytical expressions for prediction accuracies (PAs) for these traits are derived for simplified scenarios, revealing their dependence on genetic and phenotypic variances, and the distribution of related individuals within and between contact groups. PAs for infectivity are found to be critically dependent on the size of contact groups. Validation of the methodology with data from simulated epidemics demonstrates good agreement between numerically generated PAs and analytical predictions. Genetic correlations between infectivity and other traits substantially increase trait PAs. Incomplete data (e.g. time censored or infrequent sampling) generally yield only small reductions in PAs, except for when infection times are completely unknown, which results in a substantial reduction.ConclusionsThe method presented can estimate genetic parameters for host susceptibility, infectivity and recoverability from individual disease records. The freely available SIRE 2.0 software provides a valuable extension to SIRE 1.0 for estimating host polygenic effects underlying infectious disease transmission. This tool will open up new possibilities for analysis and quantification of genetic determinates of disease dynamics.

Novel insights into the genetic architecture and mechanisms of host/microbiome interactions from a multi-cohort analysis of outbred laboratory rats.

The intestinal microbiome influences health and disease. Its composition is affected by host genetics and environmental exposures. Understanding host genetic effects is critical but challenging in humans, due to the difficulty of detecting, mapping and interpreting them. To address this, we analysed host genetic effects in four cohorts of outbred laboratory rats exposed to distinct but controlled environments. We found that polygenic host genetic effects were consistent across environments. We identified three replicated microbiome-associated loci. One involved a sialyltransferase gene and Paraprevotella and we found a similar association, between ST6GAL1 and Paraprevotella , in a human cohort. Given Paraprevotella 's known immunity-potentiating functions, this suggests ST6GAL1 's effects on IgA nephropathy and COVID-19 breakthrough infections may be mediated by Paraprevotella . Moreover, we found evidence of indirect genetic effects on microbiome phenotypes, which substantially increased their total genetic variance. Finally, we identified a novel mechanism whereby indirect genetic effects can contribute to "missing heritability".

Root hair developmental regulators orchestrate drought triggered microbiome changes and the interaction with beneficial Rhizobiaceae

Drought is one of the most serious abiotic stresses, and emerging evidence suggest plant microbiome affects plant drought tolerance. However, there is a lack of genetic evidence regarding whether and how plants orchestrate the dynamic assembly of the microbiome upon drought. By utilizing mutants with enhanced or decreased root hair densities, we find that root hair regulators also affect drought induced root microbiome changes. Rhizobiaceae is a key biomarker taxa affected by root hair related mutants. We isolated and sequenced 1479 root associated microbes, and confirmed that several Rhizobium strains presented stress-alleviating activities. Metagenome, root transcriptome and root metabolome studies further reveal the multi-omic changes upon drought stress. We knocked out an ornithine cyclodeaminase (ocd) gene in Rhizobium sp. 4F10, which significantly dampens its stress alleviating ability. Our genetic and integrated multi-omics studies confirm the involvement of host genetic effects in reshaping a stress-alleviating root microbiome during drought, and provide mechanistic insights into Rhizobiaceae mediated abiotic stress protection.

Effect of host genetics on gut microbiota composition in an italian honeybee breeding population

Honeybees host a specialised gut microbiota composed of five ever-present bacteria, which undergo seasonal variation in their proportions. The objective of this study was to investigate how host genetics can affect the microbial composition of the honeybee gut over a 5-month sampling period. Seventy-seven colonies from eight maternal genetic lines were sampled from a breeding population located in Lombardy, Italy. The colonies have been selected since 2015 for three different traits, using isolated mating stations for reproduction. Worker bees were sampled three times: June, July and October 2021. From each colony, gut from ten worker bees were pooled, and the V3-V4 region of the 16S rRNA gene was amplified and sequenced. Statistical analyses were conducted in the R environment to assess the impact of genetic lines, timepoints, and their interaction on α-diversity and β-diversity. Results for α-diversity showed a significant effect of genetic line on the Simpson index, as well as a consistent effect of the timepoint. Specifically, genetic line H showed a lower Simpson index, and this line also produced less honey in the same years, suggesting a genetic influence on both microbiota richness and honey yield. For β-diversity, results revealed that the month of sampling had the strongest effect, while no significant differences were identified for the genetic line or their interaction.

Microbial diversity and biogeography across gastrointestinal tracts of Takifugu pufferfish revealed by full-length 16S amplicon sequencing

Microbial diversity and biogeography across gastrointestinal tracts of Takifugu pufferfish revealed by full-length 16S amplicon sequencing

UNDERSTANDING THE IMPACT OF DIET, HOST GENETICS AND EARLY LIFE INTERVENTIONS ON RUMEN MICROBIOME

The rumen microbiome often considered as the ruminant's second genome, facilitates the transformation of low quality feeds into high quality protein food (meat and milk) and other valuable animal products. These microbes alter the ruminal environment and help produce substrates for the host’s energy and body requirements. Several key factors influence rumen microbiota and fermentation, including diet, host genetics, and early life interventions. The potential to manipulate the rumen microbiome and meet global livestock challenges through animal breeding and introduction of dietary interventions during early life have recently emerged as promising new technologies. Advances in computational tools, high-throughput sequencing technologies and cultivation-independent “omics” approaches have provided profound insights into the rumen microbiome world, wherein a consortium of archaea, bacteria, protozoa, fungi, and viruses exist and interact. This will ultimately provide the knowledge framework needed to solve current and future ruminant livestock challenges. Understanding the effect of diet, host genetics, and early life interventions on the rumen microbiome is crucial for optimizing ruminant animal health, productivity, and efficiency of feed utilization while minimizing the environmental impact of ruminant production.

Analysis of hepatic lentiviral vector transduction; implications for preclinical studies and clinical gene therapy protocols.

Lentiviral vector-transduced T-cells were approved by the FDA as gene therapy anti-cancer medications. Little is known about the host genetic variation effects on the safety and efficacy of the lentiviral vector gene delivery system. To narrow this knowledge-gap, we characterized hepatic gene delivery by lentiviral vectors across the Collaborative Cross (CC) mouse genetic reference population. For 24 weeks, we periodically measured hepatic luciferase expression from lentiviral vectors in 41 CC mouse strains. Hepatic and splenic vector copy numbers were determined. We report that CC mouse strains showed highly diverse outcomes following lentiviral gene delivery. For the first time, moderate correlation between mouse strain-specific sleeping patterns and transduction efficiency was observed. We associated two quantitative trait loci (QTLs) with intra-strain variations in transduction phenotypes, which mechanistically relates to the phenomenon of metastable epialleles. An additional QTL was associated with the kinetics of hepatic transgene expression. Genes comprised in the above QTLs are potential targets to personalize gene therapy protocols. Importantly, we identified two mouse strains that open new directions in characterizing continuous viral vector silencing and HIV latency. Our findings suggest that wide-range patient-specific outcomes of viral vector-based gene therapy should be expected. Thus, novel escalating dose-based clinical protocols should be considered.

Caenorhabditis elegans as a Convenient Animal Model for Microbiome Studies.

Microbes constitute the most prevalent life form on Earth, yet their remarkable diversity remains mostly unrecognized. Microbial diversity in vertebrate models presents a significant challenge for investigating host-microbiome interactions. The model organism Caenorhabditis elegans has many advantages for delineating the effects of host genetics on microbial composition. In the wild, the C. elegans gut contains various microbial species, while in the laboratory it is usually a host for a single bacterial species. There is a potential host-microbe interaction between microbial metabolites, drugs, and C. elegans phenotypes. This mini-review aims to summarize the current understanding regarding the microbiome in C. elegans. Examples using C. elegans to study host-microbe-metabolite interactions are discussed.

SARS-CoV-2 strains bearing Omicron BA.1 spike replicate in C57BL/6 mice.

SARS-CoV-2, the cause of the COVID pandemic, is an RNA virus with a high propensity to mutate. Successive virus variants, including variants of concern (VOC), have emerged with increased transmission or immune escape. The original pandemic virus and early variants replicated poorly, if at all, in mice at least partly due to a mismatch between the receptor binding domain on the viral spike protein and the murine angiotensin converting enzyme 2 (ACE2). Omicron VOC emerged in late 2021 harboring > 50 new mutations, 35 of them in the spike protein. This variant resulted in a very large wave of infections, even in the face of prior immunity, albeit being inherently less severe than earlier variants. Reflecting the lower severity reported in humans, Omicron displayed attenuated infection in hamsters and also in the K18-hACE2 mouse model. K18-hACE2 mice express both the human ACE2 as well as the endogenous mouse ACE2. Here we infected hACE2 knock-in mice that express only human ACE2 and no murine ACE2, or C57BL/6 wildtype mice with SARS-CoV-2 D614G (first-wave isolate), Delta or Omicron BA.1 variants and assessed infectivity and downstream innate immune responses. While replication of SARS-CoV-2 Omicron was lower in the lungs of hACE2 knock-in mice compared with SARS-CoV-2 D614G and VOC Delta, it replicated more efficiently than the earlier variants in C57BL/6 wildtype mice. This opens the opportunity to test the effect of host genetics on SARS-CoV-2 infections in wildtype mice. As a proof of principle, we tested Omicron infection in mice lacking expression of the interferon-alpha receptor-1 (IFNAR1). In these mice we found that loss of type I IFN receptor signaling resulted in higher viral loads in the lungs were detected. Finally, using a chimeric virus of first wave SARS-CoV-2 harboring the Omicron spike protein, we show that Omicron spike increase infection of C57BL/6 wildtype mice, but non-spike genes of Omicron confer attenuation of viral replication. Since this chimeric virus efficiently infected C57BL/6 wildtype mice, and replicated in their lungs, our findings illustrate a pathway for genetic mapping of virushost interactions during SARS-CoV-2 infection.

Symbiodiniaceae diversity varies by host and environment across thermally distinct reefs.

Endosymbiotic dinoflagellates (Symbiodiniaceae) influence coral thermal tolerance at both local and regional scales. In isolation, the effects of host genetics, environment, and thermal disturbances on symbiont communities are well understood, yet their combined effects remain poorly resolved. Here, we investigate Symbiodiniaceae across 1300 km in Australia's Coral Sea Marine Park to disentangle these interactive effects. We identified Symbiodiniaceae to species-level resolution for three coral species (Acropora cf humilis, Pocillopora verrucosa, and Pocillopora meandrina) by sequencing two genetic markers of the symbiont (ITS2 and psbAncr), paired with genotype-by-sequencing of the coral host (DArT-seq). Our samples predominantly returned sequences from the genus Cladocopium, where Acropora cf humilis affiliated with C3k, Pocillopora verrucosa with C. pacificum, and Pocillopora meandrina with C. latusorum. Multivariate analyses revealed that Acropora symbionts were driven strongly by local environment and thermal disturbances. In contrast, Pocillopora symbiont communities were both partitioned 2.5-fold more by host genetic structure than by environmental structure. Among the two Pocillopora species, the effects of environment and host genetics explained four times more variation in symbionts for P. meandrina than P. verrucosa. The concurrent bleaching event in 2020 had variable impacts on symbiont communities, consistent with patterns in P. verrucosa and A. cf humilis, but not P. meandrina. Our findings demonstrate how symbiont macroscale community structure responses to environmental gradients depend on host species and their respective population structure. Integrating host, symbiont, and environmental data will help forecast the adaptive potential of corals and their symbionts amidst a rapidly changing environment.

Mechanisms of hepatic steatosis in chickens: integrated analysis of the host genome, molecular phenomics and gut microbiome.

Hepatic steatosis is the initial manifestation of abnormal liver functions and often leads to liver diseases such as nonalcoholic fatty liver disease in humans and fatty liver syndrome in animals. In this study, we conducted a comprehensive analysis of a large chicken population consisting of 705 adult hens by combining host genome resequencing; liver transcriptome, proteome, and metabolome analysis; and microbial 16S ribosomal RNA gene sequencing of each gut segment. The results showed the heritability (h2 = 0.25) and duodenal microbiability (m2 = 0.26) of hepatic steatosis were relatively high, indicating a large effect of host genetics and duodenal microbiota on chicken hepatic steatosis. Individuals with hepatic steatosis had low microbiota diversity and a decreased genetic potential to process triglyceride output from hepatocytes, fatty acid β-oxidation activity, and resistance to fatty acid peroxidation. Furthermore, we revealed a molecular network linking host genomic variants (GGA6: 5.59-5.69 Mb), hepatic gene/protein expression (PEMT, phosphatidyl-ethanolamine N-methyltransferase), metabolite abundances (folate, S-adenosylmethionine, homocysteine, phosphatidyl-ethanolamine, and phosphatidylcholine), and duodenal microbes (genus Lactobacillus) to hepatic steatosis, which could provide new insights into the regulatory mechanism of fatty liver development.

Personalised medicine based on host genetics and microbiota applied to colorectal cancer.

Personalised medicine based on host genetics and microbiota applied to colorectal cancer.

Host and rumen microbiome contributions to feed efficiency traits in Holstein cows

It is now widely accepted that dairy cow performance is influenced by both the host genome and rumen microbiome composition. The contributions of the genome and the microbiome to the phenotypes of interest are quantified by heritability (h2) and microbiability (m2), respectively. However, if the genome and microbiome are included in the model, then the h2 reflects only the contribution of the direct genetic effects quantified as direct heritability (hd2), and the holobiont effect reflects the joint action of the genome and the microbiome, quantified as the holobiability (ho2). The objectives of this study were to estimate h2, hd2,m2, and ho2 for dry matter intake, milk energy, and residual feed intake; and to evaluate the predictive ability of different models, including genome, microbiome, and their interaction. Data consisted of feed efficiency records, SNP genotype data, and 16S rRNA rumen microbial abundances from 448 mid-lactation Holstein cows from 2 research farms. Three kernel models were fit to each trait: one with only the genomic effect (model G), one with the genomic and microbiome effects (model GM), and one with the genomic, microbiome, and interaction effects (model GMO). The model GMO, or holobiont model, showed the best goodness-of-fit. The hd2 estimates were always 10% to 15% lower than h2 estimates for all traits, suggesting a mediated genetic effect through the rumen microbiome, and m2 estimates were moderate for all traits, and up to 26% for milk energy. The ho2 was greater than the sum of hd2 and m2, suggesting that the genome-by-microbiome interaction had a sizable effect on feed efficiency. Kernel models fitting the rumen microbiome (i.e., models GM and GMO) showed larger predictive correlations and smaller prediction bias than the model G. These findings reveal a moderate contribution of the rumen microbiome to feed efficiency traits in lactating Holstein cows and strongly suggest that the rumen microbiome mediates part of the host genetic effect.

Host Genetic Background Effect on Body Weight Changes Influenced by Heterozygous Smad4 Knockout Using Collaborative Cross Mouse Population.

Obesity and its attendant conditions have become major health problems worldwide, and obesity is currently ranked as the fifth most common cause of death globally. Complex environmental and genetic factors are causes of the current obesity epidemic. Diet, lifestyle, chemical exposure, and other confounding factors are difficult to manage in humans. The mice model is helpful in researching genetic BW gain because genetic and environmental risk factors can be controlled in mice. Studies in mouse strains with various genetic backgrounds and established genetic structures provide unparalleled opportunities to find and analyze trait-related genomic loci. In this study, we used the Collaborative Cross (CC), a large panel of recombinant inbred mouse strains, to present a predictive study using heterozygous Smad4 knockout profiles of CC mice to understand and effectively identify predispositions to body weight gain. Male C57Bl/6J Smad4+/- mice were mated with female mice from 10 different CC lines to create F1 mice (Smad4+/-x CC). Body weight (BW) was measured weekly until week 16 and then monthly until the end of the study (week 48). The heritability (H2) of the assessed traits was estimated and presented. Comparative analysis of various machine learning algorithms for predicting the BW changes and genotype of mice was conducted. Our data showed that the body weight records of F1 mice with different CC lines differed between wild-type and mutant Smad4 mice during the experiment. Genetic background affects weight gain and some lines gained more weight in the presence of heterozygous Smad4 knockout, while others gained less, but, in general, the mutation caused overweight mice, except for a few lines. In both control and mutant groups, female %BW had a higher heritability (H2) value than males. Additionally, both sexes with wild-type genotypes showed higher heritability values than the mutant group. Logistic regression provides the most accurate mouse genotype predictions using machine learning. We plan to validate the proposed method on more CC lines and mice per line to expand the literature on machine learning for BW prediction.

Association between the skin microbiome and MHC class II diversity in an amphibian.

Microbiomes play an important role in determining the ecology and behaviour of their hosts. However, questions remain pertaining to how host genetics shape microbiomes, and how microbiome composition influences host fitness. We explored the effects of geography, evolutionary history and host genetics on the skin microbiome diversity and structure in a widespread amphibian. More specifically, we examined the association between bacterial diversity and composition and the major histocompatibility complex class II exon 2 diversity in 12 moor frog (Rana arvalis) populations belonging to two geographical clusters that show signatures of past and ongoing differential selection. We found that while bacterial alpha diversity did not differ between the two clusters, MHC alleles/supertypes and genetic diversity varied considerably depending on geography and evolutionary history. Bacterial alpha diversity was positively correlated with expected MHC heterozygosity and negatively with MHC nucleotide diversity. Furthermore, bacterial community composition showed significant variation between the two geographical clusters and between specific MHC alleles/supertypes. Our findings emphasize the importance of historical demographic events on hologenomic variation and provide new insights into how immunogenetic host variability and microbial diversity may jointly influence host fitness with consequences for disease susceptibility and population persistence.

Combined effects of host genetics and diet on porcine intestinal fungi and their pathogenic genes.

As research on gut microbes progresses, it becomes increasingly clear that a small family of microbiota--fungi, plays a crucial role in animal health. However, little is known about the fungal composition in the pig intestine, especially after a dietary fiber diet and hybrid genetics, and the changes in host pathogenicity-associated genes they carry. The purpose of this study is to investigate the effects of diet and genetics on the diversity and structure of porcine intestinal fungi and to describe, for the first time, the host pathogenicity-related genes carried by porcine intestinal fungi. Samples of colonic contents were collected for metagenomic analysis using a 3 × 2 parsing design, where three pig breeds (Taoyuan, Duroc, and crossbred Xiangcun) were fed high or low fiber diets (n = 10). In all samples, we identified a total of 281 identifiable fungal genera, with Ascomycota and Microsporidia being the most abundant fungi. Compared to Duroc pigs, Taoyuan and Xiangcun pigs had higher fungal richness. Interestingly, the fiber diet significantly reduced the abundance of the pathogenic fungus Mucor and significantly increased the abundance of the fiber digestion-associated fungus Neocallimastix. Pathogenic fungi exert their pathogenicity through the genes they carry that are associated with host pathogenicity. Therefore, we obtained 839 pathogenicity genes carried by the spectrum of fungi in the pig intestine by comparing the PHI-base database. Our results showed that fungi in the colon of Taoyuan pigs carried the highest abundance of different classes of host pathogenicity-related genes, and the lowest in Duroc pigs. Specifically, Taoyuan pigs carried high abundance of animal pathogenicity-related genes (CaTUP1, CPAR2_106400, CaCDC35, Tfp1, CaMNT2), and CaTUP1 was the key gene for Candida pathogenicity. The intestinal fungal composition of crossbred Xiangcun pigs and the abundance of host pathogenicity-associated genes they carried exhibited a mixture of characteristics of Taoyuan and Duroc pigs. In conclusion, our results provide the first comprehensive report on the effects of dietary fiber and genetics on the composition of intestinal fungi and the host-associated pathogenicity genes they carry in pigs. These findings provide a reference for subsequent pig breeding and development of anti-pathogenic fungal drugs.

Combined effect of microbially derived cecal SCFA and host genetics on feed efficiency in broiler chickens

BackgroundImproving feed efficiency is the most important goal for modern animal production. The regulatory mechanisms of controlling feed efficiency traits are extremely complex and include the functions related to host genetics and gut microbiota. Short-chain fatty acids (SCFAs), as significant metabolites of microbiota, could be used to refine the combined effect of host genetics and gut microbiota. However, the association of SCFAs with the gut microbiota and host genetics for regulating feed efficiency is far from understood.ResultsIn this study, 464 broilers were housed for RFI measuring and examining the host genome sequence. And 300 broilers were examined for cecal microbial data and SCFA concentration. Genome-wide association studies (GWAS) showed that four out of seven SCFAs had significant associations with genome variants. One locus (chr4: 29414391–29417189), located near or inside the genes MAML3, SETD7, and MGST2, was significantly associated with propionate and had a modest effect on feed efficiency traits and the microbiota. The genetic effect of the top SNP explained 8.43% variance of propionate. Individuals with genotype AA had significantly different propionate concentrations (0.074 vs. 0.131 μg/mg), feed efficiency (FCR: 1.658 vs. 1.685), and relative abundance of 14 taxa compared to those with the GG genotype. Christensenellaceae and Christensenellaceae_R-7_group were associated with feed efficiency, propionate concentration, the top SNP genotypes, and lipid metabolism. Individuals with a higher cecal abundance of these taxa showed better feed efficiency and lower concentrations of caecal SCFAs.ConclusionOur study provides strong evidence of the pathway that host genome variants affect the cecal SCFA by influencing caecal microbiota and then regulating feed efficiency. The cecal taxa Christensenellaceae and Christensenellaceae_R-7_group were identified as representative taxa contributing to the combined effect of host genetics and SCFAs on chicken feed efficiency. These findings provided strong evidence of the combined effect of host genetics and gut microbial SCFAs in regulating feed efficiency traits.6SQoLRD3ZqDatjTJpeYTJEVideo