Gut virome and microbiome dynamics before and after SARS-CoV-2 infection in women living with HIV and their infants

Microbiome perturbations can have long-term effects on health. The dynamics of the gut microbiome and virome in women living with HIV (WLHIV) and their newborn infants is poorly understood. Here, we performed metagenomic sequencing analyses on longitudinal stool samples including 23 mothers (13 WLHIV, 10 HIV-negative) and 12 infants that experienced SARS-CoV-2 infection with mild disease, as well as 40 mothers (18 WLHIV, 22 HIV-negative) and 60 infants that remained SARS-CoV-2 seronegative throughout the study follow-up. Regardless of HIV or SARS-CoV-2 status, maternal bacterial and viral profiles were distinct from infants. Using linear mixed effects models, we showed that while the microbiome alpha diversity trajectory was not significantly different between SARS-CoV-2 seropositive and seronegative women. However, seropositive women’s positive trajectory while uninfected was abruptly reversed after SARS-CoV-2 infection (p = 0.015). However, gut virome signatures of women were not associated with SARS-CoV-2. Alterations in infant microbiome and virome diversities were generally not impacted by SARS-CoV-2 but were rather driven by development. We did not find statistically significant interactions between HIV and SARS-CoV-2 on the gut microbiome and virome. Overall, our study provides insights into the complex interplay between maternal and infant bacterial microbiome, virome, and the influence of SARS-CoV-2 and HIV status.


INTRODUCTION
Disruptions in healthy gut microbiota can have lasting consequences [1][2][3][4] , and there is growing evidence that viral infections can lead to signi cant alterations in both the gut bacterial microbiome and virome 5- 8 .For example, people living with HIV have shown increased risk of in ammation, altered virome and bacterial microbiome, and increased pathogenic viral and bacterial infections, even during antiretroviral treatment (ART) [8][9][10] .In addition, children who are HIV-exposed but uninfected (HEU) have been reported to have an altered gut microbiome compared to HIV-unexposed and uninfected (HUU) children 11,12 .SARS-CoV-2 infection has also been observed to alter the gut microbiome for both adults and infants and can cause long lasting microbiota disruption 7,[13][14][15][16] .Some studies have found speci c gut species to be associated with severity of SARS-CoV-2 symptoms, ranging from mild/asymptomatic to severe.For example, Faecalibacterium prausnitzii, Bi dobacterium bi dum, and Akkermansia muciniphila were negatively associated with disease severity 7,14 .Other studies have reported overall lower gut microbiome alpha diversity and richness during versus after SARS-CoV-2 infection, and while the richness and alpha diversity increased after recovery, richness was still lower six months after SARS-CoV-2 infection when compared to uninfected controls 13,17 .To date, few studies include virome sequence data; however, there is some evidence that SARS-CoV-2 impacts the intestinal virome as well [18][19][20] .
Given that both HIV and SARS-CoV-2 have been shown to alter gut microbiota, and that more than 39 million people have been living with HIV globally during the SARS-CoV-2 pandemic 21 , studies are needed to understand whether infection with both viruses has additional effects on the gut microbiota.
This could have impactful consequences as gut microbiota are implicated in clinical outcomes such as the risk of persistent diarrhea diseases, one of the leading causes of childhood disability-adjusted life years 22 .This longitudinal study investigates the impact of SARS-CoV-2 on the gut bacterial microbiome and virome of a mother-infant cohort in Kenya that includes women living with HIV (WLHIV) and women without HIV and their HIV-exposed and unexposed infants.We hypothesized that the gut bacterial microbiome and DNA virome of mothers and infants would be altered due to SARS-CoV-2 infection, both at time of infection as well as post infection.This unique cohort additionally also allowed us to investigate whether maternal HIV infection contributes additional alterations to the gut bacterial microbiome and/or virome in mothers and their infants during and after SARS-CoV-2 infection.

Study population
All infants with maternal consent for SARS-CoV-2 testing with stool (for bacterial microbiome and virome sequencing) and blood samples (for SARS-CoV-2 serology) collected between January 2020 and December 2020 were included; maternal samples were only included if their related infant was included in this analysis.SARS-CoV-2 infection was determined by serology assays detecting antibodies to SARS-CoV-2 nucleocapsid protein, as described previously 23 .Of 72 eligible infants, 60 were negative and 12 were positive for SARS-CoV-2 in 2020.Eighteen WLHIV and 22 HIV-negative women remained negative for SARS-CoV-2 (controls), while the remaining 13 WLHIV and 10 HIV-negative women tested positive for SARS-CoV-2 in 2020.Participants that had SARS-CoV-2 infection were primarily asymptomatic or mildly symptomatic, with no hospitalizations as previously described 23 .Of the 95 ever seropositive SARS-CoV-2 samples, there were 54 pre-infection samples and 41 post-infection samples.Stool samples were collected from the study participants during scheduled infant wellness checks at day 4 (month 1), week 6 (month 2), week 10 (month 3), month 6, month 12, month 15, month 18 and month 21 (Fig. 1B).Samples were stored at -80ºC and maintained in cold chain during transport from Kenya to the United States.

Bacterial and viral metagenomic sequencing
Approximately 200mg of stool was weighed out and diluted to 1:6 with SM Buffer then was vortexed at max speed for three minutes to fully homogenize.Samples were centrifuged at 4° for ve minutes at 20,000g.The centrifuged pellet (metagenomics) was taken through Qiagen's DNeasy PowerSoil Pro Kit following kit protocol recommendations and then followed by Illumina's DNA prep for library builds and sequenced on a NextSeq 2000 (2x150).The supernatant (viral) was ltered by a 0.20µm lter and then processed by a VLP enrichment before extractions.A mastermix of Benzonase (2µl), Baseline Zero 10x Buffer (100µ), and Baseline Zero DNASE (4µl) was added to each sample and heated for 37° for one hour.
After the heat treatment 1mL was transferred into bioMérieux's EMAG for total nucleic acid (TNA) extraction.The TNA was ampli ed with GenomiPhi V2 (GE Healthcare) before moving into library builds with DNA Prep (Illumina) and sequencing with a NextSeq 2000 (2x150).Controls of SM Buffer spiked with lambdavirus DNA were used to assess cross-sample contamination during ampli cation and sequencing.

Bacterial microbiome and virome analysis
Illumina sequencing reads (2x150) paired end reads, an average of 28,749,393 ± 28,076,646 bacterial metagenomic reads, were quality ltered using BBtools and cutadapt 24,25 .These reads were then input into krakenuniq to output read counts for assigned bacterial taxa.We then used DBSCAN, a clustering algorithm, on 10% of our samples (n = 31) to obtain the cutoff for optimal number of unique k-mer assigned per taxon for false positives and true positives 26 .For our data, anything below 5,683 number of k-mers per taxon was removed.We also used R package decontam, as previously described 27 , and removed the default called contaminants 28 .As we only have two features, reads and k-mers, DBSCAN was used as our clustering models, as it is robust at handling outliers and as well as work well with small number of features with large number of samples 26 .
Illumina sequencing reads (2x150) paired end reads; an average of 23,552,078 ± 24,293,278 DNA viral metagenomic reads, were quality ltered using BBtools and cutadapt.Quality ltered paired reads for each sample were used to build contigs with metaSPAdes for each sample (DNA stool sample = 303, control n = 32) 29 .We built a total of 5,536, 238 DNA contigs from stool samples.We then removed human contigs using bowtie2 (5,415,917 DNA contigs), clustered the remaining contigs via cd-hit (2,621,693 DNA contigs) and then ltered by minimum contig length of 1000 for DNA bp (267,202 DNA contigs) 30,31 .Theses contigs were then input into Cenote-Taker 2, VirSorter 2 and tblastx/blastn (GVD/NCBI NT database) to identify viral contig candidates [32][33][34][35] .After the contigs initially passed each tool, we then used checkV for a nal contig quality ltering and provirus screening 36 .We used contigs with at least medium quality and those which had more viral contigs then host contigs as well as all proviruses identi ed, as per checkV.This gave us a total of (11,500 viral DNA contigs).
The viral contigs were then used to run blastx against viral RefSeq + Neighboring sequences database (downloaded 2020).Using blastx output, we then used taxonomizr was to assign taxonomy to each contig (family level) 35,37 .The nal DNA contigs were then used as databases for which all stool sample QC reads were mapped against to get DNA virome matrix for all subsequent analysis.We used R package decontam, and removed the default called contaminants for DNA viruses and used RPKM (reads per kilobase million) to normalize for contig length.

Linear mixed effects and PERMANOVA models
We used linear mixed-effects (LME) models (R package nlme, version 3.1-148) to compare changes in richness and alpha diversity across post-partum time (mothers) or month of life (infants) while accounting for repeated measurements.We used PERMANOVA (vegan, permute and Adonis in R) to assess changes in beta diversity as measured by unweighted and weighted Bray-Curtis distances.Person code (mother or infant), maternal HIV status, post-partum time/month of life (age), time since weaning, antibiotic use, time since SARS-CoV-2 infection were included in the LME and PERMANOVA models to account for exposures and/or possible confounding.For infants, time-since-weaning is an important time variable in addition to age, as introduction to solids has a large impact on the gut microbes in infants 38,39 .Because infant weaning was collinear with age (Pearson r = 0.94, p < 0.0001), we included them in models separately.For the models we used two different methods to classify SARS-CoV-2 samples: rst, we used SARS-CoV-2 infection status at sample collection time and second, we used if patients were ever versus never SARS-CoV-2 seropositive throughout follow-up in the year 2020.This method allowed us to code samples as controls, pre-SARS-CoV-2 infection, and post-SARS-CoV-2 infection in the models.We also measured time since SARS-CoV-2 infection for women who were ever seropositive to see if there were differences in the gut microbiota over time after infection.We rst ran LME and PERMANOVA (Adonis) models with to assess whether outcomes differed between mothers and infants and inform if subsequent analyses should be strati ed by person.After stratifying by person, we included an interaction between maternal HIV status and SARS-CoV-2 status to assess the need for further strati cation by HIV status in women.
To assess if there was a change in the richness, alpha and beta diversity of SARS-CoV-2 women in comparison to controls, we modeled an interaction term between SARS-CoV-2 and time postpartum/infant month of life.We also removed the interaction term to re-run the LME and PERMANOVA models to test if for differences in alpha diversity, richness and beta-diversity due to the covariables (metadata) within the model.For the women who were ever SARS-CoV-2 seropositive, we created interactive models for SARS-CoV-2 infection status at time of collection and time to compare the changes that occur in the alpha diversity and richness before and after seroconversion.We then wanted to analyze if there was a change in the rst ever positive SARS-CoV-2 samples from all SARS-CoV-2 negative samples.Only the rst positive samples were kept in the models.Linear and PCoA plots were plotted using ggplot2 (version 3.3.1).

Community states
To obtain the community states present in the stool samples of this study we clustered our weighted beta diversity distance matrix with k-means method for the bacteria.We rst used the R package factoextra (version 1.0.7) to determine the optimal number of clusters and then used stats function k-means to cluster the relative abundance at bacterial species level into ve groups.To determine associations between community states and time, infant/mother, maternal HIV status, SARS-CoV-2 infection, or antibiotic use, we used R package mclogit (version 0.8.7.2) to perform multinomial logit models with random effects for individual participants; the Benjamini-Hochberg method was used to correct for multiple comparisons.We were unable to cluster the DNA virome data due to high interpersonal beta diversity.We used Kruskal Wallis, while accounting for multiple comparisons, to test for signi cant differences in the most abundant viral families between mother sand infants.

Differential analysis
To nd differentiating bacteria and viruses, we created models using R package Microbiome Multivariable Association with Linear Models (MaAsLin2) with metadata and controlling for longitudinal samples per patient 40 .For bacteria and viruses separately, we used all samples to determine taxa that that differentiated mothers and infants.We used the default q-value threshold of 0.25 for signi cance.We then strati ed the samples by mother or infant and assessed other factors, including maternal HIV status, SARS-CoV-2 status, antibiotic use, postpartum time, or time since weaning, that could be associated with speci c bacteria in mothers and/or infants.We recalculated the q-value using all results outpupt le and used the updated q-value of 0.05 for signi cance per factor.Among mothers, there were no speci c bacteria signi cantly associated with SARS-CoV-2 infection, HIV status, antibiotics use or postpartum time.Among infants, differentiating bacteria taxa were signi cantly associated with age (Supplementary Fig. 1H), time since weaning (Supplementary Fig. 1I), and SARS-CoV-2 status in infants (Supplementary Fig. 1J).Viral contigs were associated with SARS-CoV-2 status at time of collection in infants (Supplementary Fig. 1K).No differentiating viral contigs were associated with HIV status, SARS-CoV-2 status or postpartum time for mothers.One contig (Redondoviridae) was found to be more abundant in mothers using antibiotics in comparison to mothers with no antibiotics.

Shared bacterial microbiome and virome
To determine if the infant bacterial microbiome and virome was becoming more similar to the maternal (adult-like) bacterial microbiome and virome, we plotted the weighted Bray-Curtis dissimilarity distances between mothers and infants by age/time postpartum.We then used linear regression to determine if there was a signi cant change in dissimilarity by maternal HIV status and SARS-CoV-2 infection status.

Humann3
To nd active pathways in the bacterial metagenomic sequences, we ran quality ltered sequences through humann3 41 using default parameters.This output gave us the abundance of pathways for the samples, which we then used for differentiation.With the pathways' abundance matrix for the stool samples, we used Maaslin2 on all samples to see differentiating pathways between mother and infant samples.We then subset the data into mother and infants and once again ran Maasline2 to test for additional metadata signi cance including antibiotic use, infant age/maternal post-partum time, maternal HIV status and time since-weaning.The resulting pathways for signi cant metadata were plotted as heatmaps using pathway relative abundance.

Study population
The Linda Kizazi Study was a prospective birth cohort study of 211 mother-infant pairs in Nairobi, Kenya from 2018-2022 (see methods) 23,42 .Between January 1-December 31, 2020, a subset of 63 mothers and 72 infants consented to SARS-CoV-2 testing and had longitudinal stool samples collected for bacterial microbiome and virome sequencing (Fig. 1A-B).Thirty-one mothers (women) were living with HIV (WLHIV) and receiving ART and 32 were HIV-negative (Fig. 1); 35 infants were HEU and 37 were HUU.SARS-CoV-2 infection timing was determined by serology testing of plasma samples collected approximately quarterly; 23 mothers and 12 infants were positive for SARS-CoV-2 antibodies at any time during study follow-up, which was prior to the availability of SARS-CoV-2 rapid tests or vaccines in Kenya 23,42 .
When strati ed by SARS-CoV-2 seropositivity, we found that there was no signi cant difference in infant age, gestational age at birth, time from weaning, delivery route or maternal CD4 count; however, antibiotic use, maternal age and post-partum time at sample collection were signi cantly different (Table 1).When strati ed by HIV-status, we found no difference by maternal post-partum time, infant age, gestational age at birth, time from weaning or delivery route; however maternal age at study enrollment was signi cantly higher among WLHIV (Table 1).

DNA virome and bacterial microbiome differences between mothers and their infants
We performed metagenomic sequencing for bacteria and DNA viruses on 306 stool samples collected longitudinally from the study participants (Fig. 1B).One maternal sample for the bacterial analysis and 3 infant samples for the DNA viral analysis were excluded due to low sequencing read depth (< 200K reads).An average of 14,147,662 ± 13,612,749 bacterial metagenomic reads per sample and 4,498,593 ± 3,826,239 DNA viral metagenomic reads per sample were analyzed.
Previous studies have shown that adult and infant gut microbiomes differ substantially 27,[43][44][45][46] .Using linear mixed effects models (LME) and PERMANOVA to compare microbiome diversity, we found that maternal and infant samples had signi cantly different bacterial richness (p = 0.0002) and alpha diversity (p < 0.0001), but not beta diversity (PERMANOVA, p = 0.85).DNA virome richness also differed between mothers and infants (p = 0.006), while virome alpha and beta diversity did not (p = 0.13; p = 0.62).When comparing all infant and maternal sample Bray-Curtis distances without controlling for time, we found signi cant differences for bacterial and viral beta diversity (p < 0.001, Fig. 2A-B).Microbiome Bray-Curtis dissimilarity distance between mothers and infants decreased over time regardless of SARS-CoV-2 or maternal HIV status (p < 0.0001), indicating infants were converging toward an adult-like microbiome con guration that is resilient to these viral infections (Fig. 2C, Supplementary Fig. 1A-B).In contrast, the DNA virome beta diversity between mother and infants did not change over time (p = 0.23) and maintained high dissimilarity throughout the early life period, regardless of SARS-CoV-2 and maternal HIV status (median maternal-infant dissimilarity = 0.99, Fig. 2D, Supplementary Fig. 1C-D).

Assessing changes in microbiome and virome trajectory after SARS-CoV-2 infection
Given the dynamic nature of the microbiome, we tested the hypothesis that SARS-CoV-2 infection affected microbiome trajectory over time by LME modeling.Since a subset of women in this study were living with HIV, we assessed if there was an interaction between HIV and SARS-CoV-2.However, because there was no signi cant interaction between HIV status and SARS-CoV-2 infection on microbiome and virome richness and diversity (Supplementary Fig. 1L), women were not strati ed by HIV status in further analyses.Interaction between HIV exposure and SARS-CoV-2 could not be assessed for infants due to the limited number of HEU infants with SARS-CoV-2 infection (n = 7).
We designed interaction LME models to test if the trajectory of microbiome was altered due to SARS-CoV-2 infection over time in women.We found the trajectory changes in bacterial alpha diversity trended differently after infection (post-SARS-CoV-2) compared to SARS-CoV-2 negative women throughout study follow-up (controls), though this did not reach statistical signi cance (alpha diversity p = 0.082, Fig. 4A).
We then compared samples prior to infection (pre-SARS-CoV-2) and after infection (post-SARS-CoV-2) by including an interaction term between SARS-CoV-2 infection and time since infection.Alpha diversity increased over post-partum time before SARS-CoV-2 infection, but then markedly reversed to decrease signi cantly after infection (p = 0.015; Fig. 4B).Changes in beta diversity and bacterial richness over time were not associated with SARS-CoV-2 infection (Fig. 4C, Supplementary Fig. 2A).To assess the signi cance of individuals variable factors in women, we removed the interaction and found post-partum time and antibiotic use to be signi cant for changes in beta diversity across all women (post-partum time p = 0.020, antibiotic use p = 0.030, Supplementary Fig. 2B-C).
When assessing whether SARS-CoV-2 infection changed infants' bacterial microbiome trajectory, we found that the richness, alpha diversity and beta diversity of SARS-CoV-2 seropositive infants were not statistically signi cantly different compared to controls when measuring time by month of life (alpha diversity p = 0.10, richness p = 0.40, weighted beta diversity p = 0.14; Fig. 4D-E, Supplementary Fig. 2D), or by time since weaning (richness p = 0.63, alpha diversity p = 0.20, weighted beta diversity p = 0.093).
Because changes in the gut microbiome are associated with early life development 47,48 , we also analyzed infant samples without modeling for SARS-CoV-2 interactions.Bacterial richness, alpha diversity and beta diversity were associated with changes both by month-of-life and time since weaning (richness p < 0.0001, alpha diversity p < 0.0001, beta diversity by month-of-life p < 0.001, beta diversity by time-since-weaning p < 0.001; Supplementary Fig. 2E).These ndings strongly suggest SARS-CoV-2 infection in microbiome changes over time in adult women but not in infants, potentially due to stronger drivers of microbiome maturation associated with infant development.
Virome alpha diversity, beta diversity and richness over time were generally not associated with SARS-CoV-2 infection in either SARS-CoV-2 seropositive or seronegative women (alpha diversity p = 0.67, beta diversity p = 0.95, richness p = 0.25, Fig. 4F-G, Supplementary Fig. 2F).However, all women had increasing richness over time postpartum (p = 0.017), and women that remained seronegative for SARS-CoV-2 had a higher alpha diversity compared to women who were ever seropositive for SARS-CoV-2 (p = 0.046, Supplementary Fig. 2F-G).Infant models with interaction between SARS-CoV-2 status and month-of-life showed no signi cant associations between virome richness (p = 0.28), alpha diversity (0.075) and beta diversity (p = 0.85, Fig. 4I-J, Supplementary Fig. 2H).Similar to the gut microbiome developmental dynamics, when omitting the interaction from the model, infant virome richness, alpha diversity and beta diversity were signi cantly associated with changes by month-of-life (richness p = 0.010, alpha diversity p = 0.034, beta diversity p = 0.001, Supplementary Fig. 2I).These ndings are consistent with the dynamic changes in the gut virome during early infant development 47,49 .Together, these results indicate that the SARS-CoV-2 infection does not substantially alter the gut virome.
Assessing short term impacts of SARS-CoV-2 infection We next considered whether SARS-CoV-2 might a more pronounced on the microbiome during or immediately after infection.To test this, we compared only the rst SARS-CoV-2 seropositive samples to all seronegative samples (including samples prior to seroconversion and all samples from seronegative, uninfected controls).This approach allowed us to identify changes immediately postinfection that might be masked by the overall microbiome stability over time (i.e., prior trajectory analysis) and is more comparable to existing cross-sectional studies.Among women, we did not nd signi cant differences between SARS-CoV-2 seronegative and the rst seropositive samples in bacterial richness (p = 0.94), alpha diversity (p = 0.22), or weighted beta diversity (p = 0.095; Fig. 5A-B, Supplementary Fig. 3A).Findings were similar for infants (richness p = 0.93, alpha diversity p = 0.61, month-of-life weighted beta diversity p = 0.76, time-since-weaning weighted beta diversity p = 0.48, Fig. 5C-D, Supplementary Fig. 3B).There were also no signi cant differences between women's seronegative and rst seropositive samples in viral DNA richness (p = 0.70), alpha diversity (p = 0.29), or weighted beta diversity (p = 0.49, Fig. 5E-F, Supplementary Fig. 3C).Likewise for infants, when modeling for month-of-life, viral richness (p = 0.066), alpha diversity (p = 0.28), and beta diversity (p = 0.95), of their rst SARS-CoV-2 positive samples were not signi cantly different (Fig. 5G-H, Supplementary Fig. 3D).Thus, there was no evidence that SARS-CoV-2 infection signi cantly alters the gut microbiome and virome in mothers and infants immediately after infection.

DISCUSSION
In this study, we investigated how SARS-CoV-2 impacts the gut microbiome of women (both WLHIV and HIV-negative) and their infants.We found that SARS-CoV-2 altered the microbiome; however, the changes we observed were less pronounced than described in several previous studies that found SARS-CoV-2 alters the gut microbiome signi cantly after infection 5,7,13,14,16,17,19,20,[50][51][52][53][54] .This result could be due, in part, to the clinically mild SARS-CoV-2 cases in our study 23 .We also found that among women who were seropositive for SARS-CoV-2, bacterial alpha diversity increased before infection, though after infection the alpha diversity showed a trend to be decreasing.This result is consistent with other studies that have similarly showed alteration in the gut bacterial microbiome after SARS-CoV-2 infection 7,13,14,17 .
We also found that women who remained seronegative for SARS-CoV-2 throughout follow-up had a higher DNA virome alpha diversity then women who were ever seropositive.This change in virome diversity due to SARS-CoV-2 has been observed in previous studies, which have also found unique viral signatures associated with SARS-CoV-2 18-20 .However, unlike these studies, we did not nd any viruses that differentiated between women with and without any SARS-CoV-2 infection, which could be in uenced by study demographics.Unlike previous studies that mostly included patients from China, our study included Kenyan participants, infants, and women living with HIV.Another nding consistent with other studies was the association between antibiotic use signi cant dissimilarity in bacterial beta diversity among women [55][56][57] .Additionally, we found that both HIV and SARS-CoV-2 have impact on the gut microbiome as has been found in previous studies 8, 17,18,20,58,59 .Investigating the interaction between SARS-CoV-2 and HIV infection and its impact on gut microbiome and virome is unique to our study, albeit we did not nd any signi cant interactions.However, among SARS-CoV-2 infected women, richness trended to be decreased in WLHIV compared to HIV-negative women (p = 0.05; Supplementary Fig. 4A).
For the infants, we found that time (development) rather than SARS-CoV-2 or other factors we examined, had a stronger effect on the gut microbiome and virome.However, we were able to nd several bacteria and viruses that differentiated between infants with and without SARS-CoV-2 infection such as Longibacterium sp.KGMB06250, Faecalibacillus intestinalis and several Genomoviridae contigs.
Previous studies identi ed speci c differentiating bacteria and viruses (Faecalibaterium prausnitzii, Microviridae phages) that we did not observe 7,14,18 .Although not signi cant, we also found the bacterial alpha diversity in the SARS-CoV-2 seropositive infants trended lower than in the seronegative infants, and the rst positive samples trended towards higher viral richness than all seronegative samples (Supplementary Fig. 3D, Supplementary Fig. 4B-C).Thus, although infant age (i.e., development) was the primary driver of changes in infant gut microbes, SARS-CoV-2 infection also had a potentially subtle impact on the infants' bacteria and viruses.These ndings are comparable to a study of infants ≤ 2 years old that found bacterial alpha and beta diversity were not signi cantly in uenced by SARS-CoV-2 50 .Other studies with older children (range 8 days -17 years) showed changes in the bacterial alpha and beta diversity as well as differentiating bacteria 16,51,53 .Since the early life microbiome maturation is a dynamic process that occurs over the rst 3-4 years of life to reach an adult-like pro le, we expect to see this difference in which the impact of SARS-CoV-2 in older children is more in line with ndings in adults 43, 60 .A limitation of the study was the limited number of samples for SARS-CoV-2 positive samples for infants.We were therefore unable to determine the interaction of HIV exposure and SARS-CoV-2 infection in infants.Our results indicate that for children under 2, SARS-CoV-2 has no or limited impact on their gut bacterial and viral microbiomes as compared to drivers of developmental growth.

Declarations
Here's our ethics statement: Human subjects approvals for study procedures were obtained from the Kenyatta National Hospital-University of Nairobi Ethics and Research Committee and the University of Washington, Fred Hutchinson Cancer Center and Arizona State University Institutional Review Boards.

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