In December 2019, a mysterious viral pneumonia first developed in Wuhan, China, resulting in a huge number of fatal cases. This pneumonia, which was named COVID-19, was attributed to a novel coronavirus, SARS-CoV-2. The emerging SARS-CoV-2 mutations pose the greatest risk to human health because they could result in an increase in the COVID-19 severity or the failure of current vaccines. One of these notable mutations is the SARS-CoV-2 Delta variant (B.1.617) that was first detected in India and has rapidly expanded to 115 countries worldwide. Consequently, in this study, we performed next-generation sequencing and phylogenetic analysis of SARS-CoV-2 during the third wave of the pandemic to determine the SARS-CoV-2 variants of concern (VOC) prevalence in Egypt. We observed several mutational patterns, revealing that SARS-CoV-2 evolution has expanded in Egypt with a considerable increase in the number of VOC. Therefore, the Egyptian authorities should take an appropriate approach to investigate the compatibility of already employed vaccines with this VOC and to examine the efficacy of the existing therapeutic regimen against new SARS-CoV-2 variants. In December 2019, a mysterious viral pneumonia first developed in Wuhan, China, resulting in a huge number of fatal cases . This pnAccording to the phylogenetic analysis, coronaviruses are classified into four genera: alpha-, beta-, gamma-, and delta-coronaviruses, within the family Coronaviridae of the Nidovirales order. Consequently, SARS-CoV-2 is classified as a beta-coronavirus. The beta-coronaviruses are further classified into four lineages A to D; . At leasvia binding to human angiotensin-converting enzyme 2 (ACE 2) receptors . The samples were transported to the biological prevention department in a viral transport medium (Cat. No. A48498) at 4°C, in accordance with strict biosafety regulations.® Viral RNA Mini Kit  was Used for the Extraction of Viral RNA From Each Sample. Following the Purification of Viral RNA, Semi-Quantitative Amplification of the Extracted RNA was Performed by the Viasure® SARS-CoV-2 RT-PCR Detection Kit (ref. VS-NCO212H) Using the Ariamx RT-PCR Equipment .The Qiaamp® System . The Qubit™ RNA HS 100 Assay Kit (Cat. No. Q32852) was used to quantify RNA on a Qubit 2.0 Fluorometer. Then, complementary DNA was made using RT Primer Mix DP (BATCH No. 020402C). In addition, the whole SARS-CoV-2 genome was amplified using a multiplex PCR process. In order to eliminate any non-specific PCR products, digestion was performed. The DNA HS 100 Assay Kit (Cat.No.Q32852) was used to evaluate the quality of the library preparation.The AviSeq COV19 NGS Library Prep kit (Ref. AVG202096) was used to prepare the libraries according to the manufacturer’s instructions. Next-generation sequencing was performed using the Illumina iSeq 100™.Next-generation sequencing was conducted on 172 isolated isolates. FASTA files were generated using the online tool DECOVFor viral genome alignment, quality inspection, clade determination, and phylogenetic studies, the online tool “Nextclade” was utilized.Understanding the development and evolution of SARS-CoV-2 necessitates the use of phylogenetic trees. Molecular Evolutionary Genetics Analysis v.7.0 (MEGA7) software was used to conduct evolutionary studies . The phyIn the current study, 172 positive COVID-19 patients were selected based on clinical diagnosis, 130 (75.6%) males and 42 (24.4%) females, with an average age of 37 .The clinical picture of the participants included in the present work is presented in Based on rRT-PCR test results , 172 samples were positive, proving SARS-CoV-2 viral infection.n = 64). A total of 40 sequences were previously detected in Egypt (nucleotide identity = 100%) and had specific accession codes in the NCBI database. Twenty-four nucleotide sequences were novel and were submitted to NCBI GenBank to be provided with certain accession numbers.Next generation sequencing (NGS) was performed on 172 strains. The lengths of the resulting genomic sequences were identical to the genome length of the Wuhan-Hu-1 reference strain (NC 045512.2). The generated FASTA files were uploaded to the NCBI Standard Nucleotide BLASTn Tool, and the Betacoronavirus database was selected before running.The Nextclade Tool was used for the detection of genetic mutations in the SARS-CoV-2 genome, including S, E, M, N, ORF1a, ORF1b, ORF3a, ORF6, ORF7a, ORF7b, ORF8, and ORF9b see . The seqA rectangular phylogenetic tree constructed by the online Nextclade Tool revealed the most common clades were 20D (34.4%) and 21 J (32.8%), followed by 20I (12.5%), 20A (9.4%), and 19B (4.7%). Further investigation to detect the evolution of SARS-CoV-2 was conducted by determination of the divergence of the tested sequences in relation to Wuhan-Hu-1/2019 , revealing two patterns of spike protein mutations including (A570D- D614G- D1118H- N501Y- P681H- T716I) and (A570D- D614G- D1118H- N501Y- P681H- S982A- T716I) that were recorded in 7 sequences and in one sequence, respectively .The clade 21A (Delta) was reported in a single sequence (accession code OK354428). Furthermore, two sequences were clustered as clade 21I (Delta) with an S-gene mutational pattern (A222V- D614G- D950N- L452R- P681R- R158G- T19R- T478K- V1264L). Finally, a total of 21 sequences were clustered as 21 J (Delta) with 15 unique S-gene mutational patterns . These Dn = 29), the ORF1b gene (n = 19), the N gene (n = 18) and the ORF3a gene (n = 10).The frequency of each mutation detected in recovered variants (n = 64) is presented in The online Mutation Analysis tool, CoVsurver, was used for visualization of amino acid (aa) changes in the spike protein of the sequences under investigation.Further characterization of tested genomes was performed to determine the PANGO lineage using the online tool “Pangolin COVID-19 Lineage Assigner”.The analysis involved 65 nucleotide sequences, including the recovered genomes in the current work and the reference strain Wuhan-Hu-1. Before running the analysis, the elimination of all positions with gaps and missing data was performed. There were a total of 29,267 positions in the testing dataset. The maximum likelihood phylogenetic analysis revealed that variants under investigation are clustered into distinct groups according to their evolutionary pattern, as shown in We isolated SARS-CoV-2 from 172 patients admitted to the Army Hospital during the third wave of the pandemic between August and September 2021. We observed that males (75.6%) were more susceptible to COVID-19 infection than females (24.4%), with an approximate mean age of 37. This was in accordance with previous research conducted in Egypt during the first and second waves of COVID-19, which reported that those aged 40 to 60 were the most frequently infected . FurtherOur results regarding the follow-up of SARS-CoV-2 mutations revealed that variants of concern, such as alpha and delta variants, are expanding. Samples have been clustered into 8 different subclades, including 19A, 19B, 20A, 20B, 20D, 21A, 21I, and 21 J. The majority of samples were from the 20D and 21 J subclades. SARS-CoV-2 has evolved into new variants and their frequency in Egypt and even globally has increased dramatically and extensively . SeveralIn the present study, we are the first to formally characterize the B.1.617.2 variant in Egypt. Moreover, we reported that these B.1.617.2 variants were clustered into three subclades, including 21A (n = 1), 21I (n = 2), and 21 J (n = 22) with A222V, D178H, D178Y, D614G, D950N, E484Q, G181V, G1124R, G1167V, L452R, L1265F, P681R, Q173H, Q677H, R158G, T19R, T478K, T95I, T572I, and V1264L amino acid mutations in S-gene. Since its first detection in a sequence from India, the B.1.617.2 variant has already spread throughout India and to at least 115 countries due to its fast rate of transmission and infection in comparison with other previously detected variants . AccordiHowever, vaccination is quite efficient in reducing COVID-19 severity and preventing death, but it is less effective in preventing infection by the delta and alpha VOC . SeveralWe also detected the existence of the alpha variant (B.1.1.7) among recovered samples, with a prevalence of 19.8%. Seven mutations in the S-gene were reported in the alpha variants, including A570D, D614G, D1118H, N501Y, P681H, T716I, and S982A. Moreover, the most prevalent clade among recovered samples was 20D (66%) with A871S, A222V, A899S, D614G, L452R, Q613H, Q677H, R346S, S12F, T572I, and W152R mutations in the spike protein. Furthermore, only one sequence was grouped into the 20B clade with N501T and D614G mutations in spike protein. Seven sequences with spike protein mutations (H655Y-N501T) were grouped together as the 19B clade. The clade 20A with the S_D614G mutation was reported in 17 samples. Our findings regarding the prevalence of different clades during the third wave of the COVID-19 pandemic are consistent with previous studies conducted in Egypt and worldwide .Concerning mutations detected in the SARS-CoV-2 viral genome, the ORF1a, S, ORF1b, N, and ORF3a genes showed high-frequency mutations with 33 nonsynonymous mutations, including A570D, A1708D, D3L, D63G, D377Y, D614G, D950N, D1118H, G204R, G662S, I82T, I2230T, L452R, N501Y, P314L, P681H, P681R, P1000L, Q27*, R203K, R203M, S26L, S235F, S982A, T19R, T60A, T120I, T478K, T716I, T1001I, T3646A, and Y73C. The most common mutations in spike protein were D614G (47%), L452R (20%), Q677H (19%), and N501Y (13%). The S protein is involved in SARS-CoV-2’s entrance into the host cell. As a result, mutations in RBD result in higher transduction in a variety of cell types, increased resistance to proteolytic cleavage, increased contagiousness , and incin vitro. Q57H and G251V are the most common synonymous mutations in ORF3a and could have a beneficial impact on viral adaptation , 21A, 21I, and 21 J (delta). Several mutational patterns were observed in Egypt, revealing that SARS-CoV-2 evolution has expanded. The twenty-five isolates shown in the present study are the first fully characterized Delta variant (B.1.617.2) in Egypt. Therefore, the Egyptian Ministry of Health and Population as well as healthcare decision-makers must investigate the compatibility of already employed vaccinations with this VOC and examine the efficacy of the existing therapeutic regimen against new SARS-CoV-2 variants.The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/ The studies involving human participants were reviewed and approved by the Institutional Review Board of Princess Nourah Bint Abdul Rahman (IRB Number: 20-0457 in 2020), and after the permission from the head of the Army hospital. The patients/participants provided their written informed consent to participate in this study.RB, MS, and ME-B: conceptualization. BA, TE-M, MS, and ME-B: data curation. TE-M, MS, and ME-B: formal analysis. BA, TE-M, MS, WE, and ME-B: investigation. MS, BE-H, and AG: methodology. MS, WE, and ME-B: visualization. BA, RB, WE, and ME-B: writing–original draft. TE-M and ME-B: writing –review and editing. All authors contributed to the article and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Irrigation water is a common source of contamination that carries plant and foodborne human pathogens and provides a niche for proliferation and survival of microbes in agricultural settings. Bacterial communities and their functions in irrigation water were investigated by analyzing samples from wetland taro farms on Oahu, Hawaii using different DNA sequencing platforms. Irrigation water samples  were collected from North, East, and West sides of Oahu and subjected to high quality DNA isolation, library preparation and sequencing of the V3–V4 region, full length 16S rRNA, and shotgun metagenome sequencing using Illumina iSeq100, Oxford Nanopore MinION and Illumina NovaSeq, respectively. Illumina reads provided the most comprehensive taxonomic classification at the phylum level where Proteobacteria was identified as the most abundant phylum in the stream source and associated water samples from wetland taro fields. Cyanobacteria was also a dominant phylum in samples from tank and spring water, whereas Bacteroidetes were most abundant in wetland taro fields irrigated with spring water. However, over 50% of the valid short amplicon reads remained unclassified and inconclusive at the species level. In contrast, Oxford Nanopore MinION was a better choice for microbe classification at the genus and species levels as indicated by samples sequenced for full length 16S rRNA. No reliable taxonomic classification results were obtained while using shotgun metagenome data. In functional analyzes, only 12% of the genes were shared by two consortia and 95 antibiotic resistant genes (ARGs) were detected with variable relative abundance. Full descriptions of microbial communities and their functions are essential for the development of better water management strategies aimed to produce safer fresh produce and to protect plant, animal, human and environmental health. Quantitative comparisons illustrated the importance of selecting the appropriate analytical method depending on the level of taxonomic delineation sought in each microbiome. Irrigation water quality is a growing concern for agriculture as drainage is contaminated with agricultural runoff, wastewater overflows, and polluted storm or rainwater runoff, and irrigation waters are a potential source of plant and food-borne pathogens resulting in economic crop losses and human health risks . The micBecause of water scarcity and a simultaneous need to increase food production, there has been a shift from freshwater to alternative sources of irrigation water such as reclaimed or recycled water. However, potential health and environmental impact concerns are associated with the use of alternative water sources for irrigating the crops . TherefoWith the advancement in next generation sequencing technologies (NGS), 3rd generation NGS technology, Oxford Nanopore enables generation of long sequence read lengths, possibly sequencing full length 16S rRNA genes . Full leAlthough Polymorphic marker gene  based analyzes are useful for broad community taxonomical analysis, it did not provide functionality nor resolve the complexity of a microbiome. The shotgun metagenomic sequencing using advanced Illumina sequencing platforms have been proven to be a more reliable approach for these purposes . MetagenThis study aimed to investigate bacterial microbiota and associated gene function of different irrigation systems, mainly associated with wetland taro across the island of Oahu, Hawaii. Mountain streams are the major source of irrigation waters used by farmers to irrigate crops. The overall goal of this project is to reveal the bacterial microbiota from different water source used for irrigation, in addition to field water, which is released back into the stream after use, carrying excess fertilizer, agricultural waste, ARGs and diverse unidentified bacteria. Bacterial communities were investigated based on 16S rRNA amplicon analysis using two principally different sequencing technologies and platforms—Illumina iSeq100 and Oxford Nanopore MinION and their taxonomic compositions were compared. The functionality of all the genes in complex samples and the distribution of ARGs were also investigated using shotgun metagenomic analyses. We aim to compare different technologies and approaches considered for microbiome studies such as shotgun metagenome, short- and long-amplicon read based to provide the desired level of accuracy in resolving the microbial taxonomic composition of the samples.Irrigation source and associated taro field water samples were collected in September–November 2020, across the Island of Oahu, Hawaii . Irrigatvia MF-Millipore 0.22 μm sterile MCE membrane to trap the maximum bacterial community. The 0.22 μm membrane was used for bacterial DNA isolation using NucleoMag DNA/RNA Water Kit  following manufacturer’s instructions, with a few minor modifications to improve the DNA quantity and quality. The mechanical lysis was performed in lysis buffer MWA1 for 20 min using a vortex at full speed, followed by the addition of 25 μl of RNase (12 mg/ml stock solution); the tubes were incubated for 15 min at room temperature (RT). A lysate of 450 μl was transferred to a 1.5 ml sterile Eppendorf tube and 25 μl of NucleoMag B-beads were added, mixed and shaken for 5 min, and kept on a magnetic rack at RT. The supernatant was removed, and the pellet was washed twice with buffer MWA3, followed by a single final wash with buffer MWA4. The magnetic beads were air dried for 15 min at RT; 70 μl RNase free water was used to elute DNA from the magnetic beads. Qubit dsDNA HS kit and Qubit 4  were used to quantify the genomic DNA. The DNA replicates from each sample were pooled, due to low DNA yield from each replicate, for downstream processes and stored at −80°C.Water samples collected from each site were vacuum filtered using the Millipore All-Glass Filter Holder kit . Collected water from each replicate was filtered through Whatman filter membrane to remove coarse to medium debris, followed by filtration through a MF-Millipore 8 μm sterile mixed cellulose ester (MCE) membrane , and finally, filtered via pair-wise alignment. The chimeric reads with less than a 97% best hit similarity rate were removed using EzBioCloud non-chimeric 16S rRNA database through UCHIME (The polymerase chain reaction (PCR) was performed to amplify the V3–V4 hypervariable region of 16S rRNA gene following the reaction conditions: 94°C for 5 min; 40 cycles at 94°C for 20 s, 58°C for 30 s, and 72°C for 1 min; and the final extension at 72°C for 3 min. Primers 341F (5′-TCGTCGGCAGCGTCAGATGTGTATAAGAGACAGCCTACGGGNGGCWGCAG-3′) and 805R (5′-GTCTCGTGGGCTCGGAGATGTGTATAAGAGACAGGACTACHVGGGTATCTAATCC-3′) were used for PCR amplification . The amph UCHIME . The seqh UCHIME . Bacteriα = 0.05.Valid reads were normalized for each sample to eliminate the bias produced because of variation in total number of reads. The Wilcoxon rank-sum test was used to calculate differences between the replicates. The differences in relative abundance in phyla and genera among the samples were determined using one-way ANOVA (single factor) with the least significant difference (LSD) test at via web report generated by EPI2ME workflow.The genomic DNA of sample R-F1-E and S-F3-N was diluted to 1 ng/μl, and a total 10 μl gDNA was used for full-length 16S rRNA library preparation using 16S Barcoding Kit 1–24  according to the manufacturer’s protocol. Ten μl of input DNA (10 ng) was mixed well with 25 μl LongAmp hot Start Taq 2 × Master Mix and 5 μl of nuclease free water, afterward, 10 μl of each 16S barcode was added. The PCR was performed using following conditions: Initial denaturation at 95°C for 1 min, 25 cycles of 95°C for 20 s, 55°C for 30 s and 65°C for 2 min, with a final extension at 65°C for 5 min. Each amplified sample was purified and washed with AMPure XP beads and 70% ethanol, respectively. For each sample, barcoded libraries were prepared in duplicate and quantified using Qubit 4; libraries were pooled to a desired ratio of 50–100 fmol in 10 μl of 10 mM Tris–HCl (pH 8.0) with 50 mM NaCl, and 1 μl of Rapid adapter (RAP) was added. The pooled library was loaded on to MinION vR9.4 flow cell and sequenced following manufacturer’s instruction. The generated sequencing data were monitored in real-time using the MinKNOW software (version 4.0.20). The obtained FAST5 files were base called using MinKNOW (version 4.0.20) embedded with Guppy version 3.2.10 pipeline. The attained raw long reads were deposited as SRA data in the NCBI database under BioProject ID PRJNA856390. The generated full-length 16S rRNA sequence data were analyzed using cloud based EPI2ME (Oxford Nanopore) workflow for the identification of microbial community composition; EP2ME uses the NCBI GenBank database for taxonomic identification. The minimum and maximum read length of 1,500 and 1,600, respectively, were assigned as a quality control parameter, and Blastn was run using parameters max_target seqs = 3  with blast e-value assigned as default 0.01. Per read coverage was calculated as the number of identical matches/query length. All classified reads were filtered for > 77% accuracy and > 30% coverage, which removed invalid alignments and were normalized for analysis. Results were obtained as comma-separated values (CSV) file Q-value ≤ 38), reads with N nucleotides over 10 bp, and reads that overlapped with adapters over 15 bp. The obtained clean reads after quality control were assembled into scaftigs using MEGAHIT . To identify the biologically relevant differences between two samples, statistical analyses were performed using STAMP v 2.1.3 (DNA from two samples (R-F1-E and S-F3-N) were used for preparing DNA metagenome libraries using NEBNext Ultra DNA Library Prep Kit  following manufacturer’s instructions. The sonication-based method was used for fragmenting gDNA to the size of 350 bp. The obtained DNA fragments were end-polished, A-tailed, and ligated with full-length indexing adapters to the ends of the DNA fragments, followed by PCR amplification. The PCR products were purified using AMPure XP, and libraries were analyzed for size distribution and quantified using Agilent 2,100 Bioanalyzer  and real-time qPCR, respectively. The quantified libraries were pooled and sequenced on an Illumina NovaSeq 6,000 platform to generate paired end reads. All the procured reads were submitted in the NCBI database as SRA file under BioProject PRJNA856335. The obtained raw reads were pre-processed to trim low-quality bases with quality value  as Sequence Read Archive (SRA) under the BioProject IDs PRJNA856319, PRJNA856335 and PRJNA856390.The paired end 16S rRNA encoding gene sequences were obtained using Illumina iSeq100. After the data was pre-filtered and passed the quality check to remove low-quality, non-chimeric and non-target amplicons, the total number of valid reads with an average read length was computed  for eachBased on phylum comparison performed using valid reads obtained from two sequencing replicates, no differences were observed, therefore the first replicate (barcode1-12) was considered for further taxonomic and diversity analysis . The valBased on Good’s coverage index, the sequencing covered more than 94% of the taxonomic richness except for sample R-S1-E (92.35%), R-S2-W (91.02%) and R-S5-SE 89.97%; . A totalProchlorococcus was the most abundant genus identified in samples T-S6-N (58.3%) and S-S3-N (35.65%) collected from North Oahu. Spring field water sample S-F3-N was dominated by the genus Flavobacterium with relative abundance of 37.14%, while 16.99% Flavobacterium abundance was calculated in sample R-F1-E—the abundance remained < 1% in all the other river stream and associated field water samples. The classified reads at the genus level, with a relative abundance of < 1%, ranged between 22.32–61.87% among all samples, indicating diverse microbiota associated with different samples. The percentage of valid reads that remained unclassified varied between 4.83% (T-S6-N) and 21.55% (R-S4-SE) among all the samples  to 62.23% R-F4-SE; . A totalsolution .Non-parametric analysis of diversity indices, such as ACE, CHAO, and Jackknife, indicated higher bacterial diversity in river stream compared to associated field water samples, followed by sample S-F3-N, S-S3-N, R-S7-N, and T-S6-N . The higp = 0.009) and cluster 1 and 3 , however, no significant difference observed on pairwise comparison of cluster 2 and 3  and unweighted pair group method with arithmetic mean (UPGMA) clustering based on the Bray–Curtis dissimilarity index were performed. The beta diversity indices, based on PCoA, revealed clear distinctions between different water samples forming three distinctive clusters . ClusterFurthermore, UPGMA clustering revealed a similar clustering pattern in the dissimilarity of relative abundance of the bacterial communities . To unraSamples R-F1-E and S-F3-N were sequenced in duplicate to attain confidence and reliability in the obtained data . ReplicaLimnohabitans belonging to the family Comamonadaceae. Within the family Comamonadaceae, the genera Arcobacter, Curvibacter, Limnohabitans, and Rhodoferax were identified in both samples, with an additional two genera—Hydrogenophaga and Pelomonas—exclusively in sample R-F1-E with > 1% relative abundance. Furthermore, genus Aquirufa was recognized in sample S-F3-N with relative abundance of 25.71%, while 8.86% remained in sample R-F1-E. The bacterial genera classified with relative abundance of < 1% in total comprised 33.21 and 22.41% of bacterial community in sample R-F1-E and S-F3-N, respectively.At the phylum level, sample R-F1-E showed Bacteroidetes and Proteobacteria with relative abundance of > 1%, while sample S-F1-E was dominated with 3 phyla-Bacteroidetes, Proteobacteria and Verrucomicrobia . ClassifLimnohabitans parvus II-B4 and Aquirufa anthreingensis, respectively. Four species belonging to genus Limnohabitans—L. australis, L. curvus, L. parvus II-B4, and L. planktonicus—were identified in both the samples with variable abundance. Furthermore, 73.38 and 72.06% of the bacterial diversity was composed of the bacterial population identified with relative abundance > 1% in samples R-F1-E and S-F3-N, respectively. Full length amplicon reads that remained unclassified in samples R-F1-E and S-F3-N were 1.1 and 0.82% of the total analyzed reads, respectively.At the species level, 16 and 11 species were classified from samples R-F1-E and S-F3-N, respectively, with > 1% relative abundance . SamplesShort and full length 16S rRNA amplicon reads were obtained using Illumina iSeq100 and Oxford Nanopore MinION sequencers. The taxonomic classification results at phylum, genus and species levels were compared with different input reads , randomly extracted from total obtained valid reads–for samples R-F1-E and S-F3-N .At phylum level classification, Illumina sequenced samples R-F1-E and S-F3-N identified a greater number of phyla than MinION at different input reads . In sampThe number of species classified using long amplicon reads was higher than when using short amplicon reads . The numIn term of relative abundance, almost similar abundance patterns were obtained with each technique when 10–50 K reads were used as an input data—indicated that minimum input of 10 K reads from either Illumina iSeq100 or Oxford Nanopore MinION, can provide similar resolution with 5 times more input reads. However, with respect to the number of classified phyla, Illumina provided better outcomes compared to Oxford Nanopore, and there was no dramatic increase in number of phyla when the input reads were increased from 10 to 50 K by either sequencing technology ,B. The aA total of 5,61,183 and 4,91,726 non-redundant genes were identified from sample R-F1-E and S-F3-N, respectively, while sharing 1,24,661 (12%) unigenes between both. Despite having close microbial association indicated by PCoA analysis, the samples R-F1-E and S-F3-N were distinctively differentiated based on unique genes composition of 78 and 75%, respectively.Curvibacter, Limnohabitans, Flavobacterium, Pelomonas, Rhodobacter, Pseudarcicella, and Novosphingobium—were classified with more than 1% relative abundance, whereas only five genera—Limnohabitans, Flavobacterium, Rhodoluna, Pesudarcicella, and Novosphingobium—were classified in sample S-F3-N. Species level classification revealed 10 species with relative abundance of > 1% from both the samples. A high percentage of “others” in the metagenomic analysis could result from an incomplete database.According to the obtained abundance table of each taxonomic level, the bar plots were plotted for the top 10 classified phyla, genera, and species . At the “Others” representing the relative abundance of the reads that remain unclassified and classified with relative abundance of < 1% was higher at phylum, genus, and species level classification for both the samples sequenced using Illumina NovaSeq (shotgun reads) than Illumina iSeq100 and Oxford Nanopore MinION . Sample For better insight into the physiology of a bacterial community, the assembled metagenomic protein coding sequences were mapped against three functional databases—eggNOG, KEGG, and CAZy . Both saAnnotation based on eggNOG database revealed  that higMost of the genes represented in the KEGG pathway analysis were associated with metabolic pathways , and parq-value of 4.37e–3 and was enriched in sample S-F3-N  associated genes were most abundant with the relative abundance of 49.33 and 51.87% in sample R-F1-E and S-F3-N, respectively, followed by glycosyl transferase (GT), carbohydrate-binding modules (CBM), carbohydrate esterases (CE), auxiliary activities (AA), polysaccharide lyases PL; . STAMP ae S-F3-N . WhereasMexK, a resistance nodulation cell division (RND) antibiotic efflux pump gene, was the most abundant ARG present in both the samples , ugd (peptide resistance gene), rpoB2 (rifamycin resistance gene), kdpE (aminoglycoside resistance gene), golS (multidrug resistance gene), dfrA3 (diaminopyrimidine resistance gene), mtrD (macrolide resistance gene), Streptomyces rishiriensis parY mutant conferring resistance to aminocoumarin , Bifidobacterium ileS conferring resistance to mupirocin , and mtrA (macrolide resistance gene). The relative abundance of gene ugd, kdpE, golS, and dfrA3 was higher in sample R-F1-E, whereas mexK, rpoB2, Bbif_ileS_MUP, and mtrA were relatively higher in sample S-F3-N. Interestingly, ARG mtrD and Sris_parY_AMU were only conferred to sample R-F1-E and S-F3-N, respectively.Furthermore, the top 10 most abundant ARGs out of 95 ARGs, annotated collectively from both samples, were represented in Circos for observing overall proportion and distribution of the resistance genes in both samples . The topkdpE), antibiotic target replacement (DfrA42_TMP), and ABC antibiotic efflux pump. These potential antibiotic mechanisms were associated with the ARG that were affiliated with phyla Proteobacteria  antibiotic efflux pump, antibiotic target alteration (pmr phosphoethanolamine transferase), protein and two component regulatory system modulating antibiotic efflux  on Oahu, Hawaii. Comparative assessment of bacterial communities between samples showed distinctive discriminations based on type of water system and geographical location. It is striking to note that natural stream and associated field water samples were dominated by Proteobacteria, regardless of their geographical locations—there was a close bacterial association between the samples based on beta diversity analysis. These outcomes agreed with the previous studies conducted in Brazil  and Tokyhabitans  were sucer study  also fouassified .Furthermore, we compared the performance of long reads  obtained from Oxford Nanopore MinION with short reads ~ 300 bp) obtained from Illumina iSeq100 to assess bacterial taxonomic classification at phylum, genus, and species levels with different numbers of input reads. Results from this experimental study showed uniform trends in classification at phylum, genus, and species levels for samples, R-F1-E and S-F3-N, at 10, 20, 30, 40, and 50 K input reads . However00 bp obtMexK, a resistance nodulation cell division (RND) antibiotic efflux pump gene which can transport multiple classes of antimicrobials, contributing to multidrug resistance  can be found at: MA conceived and designed the study. DK performed the experiments, analyzed the data, and wrote the manuscript. SD performed the experiment. ZH helped in the Illumina library preparation. AA, JU, and JS helped in sample collection. MA, SD, AA, ZH, JU, JS, K-HW, SK and AMA revised the manuscript and provided ideas and support for the final submission. All authors contributed to the article and approved the submitted version.This research was funded by NIGMS of the National Institutes of Health under award number P20GM125508. This work was also supported by the USDA National Institute of Food and Agriculture, Hatch project 9038H, managed by the College of Tropical Agriculture and Human Resources.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


We use an EXT fluorescent reporter with contrasting levels of cell wall insolubilization in prx01,44,73 and PRX44-overexpressing background plants. In this study, we propose that PRX01, PRX44, and PRX73 control EXT-mediated cell wall properties during polar expansion of root hair cells.Root hair cells are important sensors of soil conditions. They grow towards and absorb water-soluble nutrients. This fast and oscillatory growth is mediated by continuous remodeling of the cell wall. Root hair cell walls contain polysaccharides and hydroxyproline-rich glycoproteins, including extensins (EXTs). Class-III peroxidases (PRXs) are secreted into the apoplastic space and are thought to trigger either cell wall loosening or polymerization of cell wall components, such as Tyr-mediated assembly of EXT networks (EXT-PRXs). The precise role of these EXT-PRXs is unknown. Using genetic, biochemical, and modeling approaches, we identified and characterized three root-hair-specific putative EXT-PRXs, PRX01, PRX44, and PRX73.  EXTs are crosslinked by class-III peroxidases (PRXs) in the Tyr-based motifs [O-glycosylation levels, as well as the presence of Tyr-mediated crosslinking in EXT and related glycoproteins, would allow them to form a dendritic glycoprotein network in the cell wall. This EXT network modulates de novo cell wall formation during embryo development [Primary cell walls are composed by polysaccharides and glycoproteins. Extensins (EXTs) belong to hydroxyproline (Hyp)-rich glycoprotein superfamily (HRGP) with multiple Ser-(Pro)d motifs ,2. EXTs d motifs ,2. Afterd motifs ,5,6. PRXd motifs  by generd motifs ,9. In add motifs , likely d motifs ,11. Howeelopment ,13 and relopment ,15 and pelopment ,16,17,18elopment ,20,21.Arabidopsis thaliana [apoROS molecules (apoH2O2) directly affect the degree of cell wall crosslinking [apoROS coupled to PRX activity enhances nonenzymatic cell wall loosening by producing oxygen radical species  and promoting growth in the hydroxylic cycle (HC). In this HC cycle, PRXs catalyze the release of hydroxyl radicals (●OH) from H2O2 after O2●- dismutation. For example, PRX36 has been reported to weaken plant cell walls in seed mucilage secreted by Arabidopsis seed coat epidermal cells [●−) pool by oxidizing singlet oxygen in the oxidative cycle (OC), thereby affecting apoH2O2 levels. Thus, several PRXs are involved in the oxidative polymerization of monolignols in the apoplast of the lignifying xylem cells  and in ., PRX17 ,28). In ., PRX17 , pectins., PRX17 ,34. Alth., PRX17 ,36,37,38., PRX17 , the in ., PRX17 . In addi., PRX17 . In addi., PRX17 ,43,44. Iprx01 prx44 prx73 , that showed shorter root hairs than Wt Col-0  that regulate polar growth of root hair cells [(apoROS) and cytoplasmatic ROS pools (cytROS). Dynamic exchange between the two ROS pools is mediated by their transport across the plasma membrane via specific aquaporins (PIPs for plasma membrane intrinsic proteins) in plant cells [prx01,44,73 root hair tips showed lower levels of cytROS  a–c. 35S:r growth d. The apWt Col-0 f. These prx01,44,73 triple mutant root hairs by transmission electron microscopy  compared to Wt controls (1.2 SD 0.3 μm Wt)  results in the reduction in cell wall thickness in growing root hairs.To analyze the impact of the peroxidase activity derived from PRX01, PRX44, and PRX73 on the ultrastructure of the cell wall, we take microphotographs of Wt and croscopy a. We fou3 μm Wt) b. This rThis implies that mis-regulation of PRX activity affects the capacity of root hairs to form normal cell walls and, as a consequence, affecting their cell elongation b.Allium cepa) cells roots, and then stably expressed in Arabidopsis root hairs . We used TOM because it is fluorescent even under acidic pH  typical ot hairs . In bothot hairs , consistth of RH , making ckground a,b. Thisd by TEM . These rprx01,44,73 triple mutant relative to Wt, and slightly higher levels of IDT in EXTs extracted from the PRX73-OE line  and isodityrosine  in EXT extracted from whole roots. We detected a significant increase in peptidyl-Tyr in the -OE line . By contproteins . In thesng rates ,50.O-glycosylation of EXTs or an increase in PRX levels may trigger a reduction in the amount of peptidyl-Tyr and IDT levels in EXTs, with a putative concomitant increase in the amounts of higher-order Tyr crosslinks (trimers as Pulcherosine and tetramers as Di-IDT), thus inhibiting root hair growth. Unfortunately, we were unable to measure the Pulcherosine and Di-IDT levels described previously in EXTs  to test this hypothesis. Further research is needed to decipher the in vivo regulation of Tyr crosslinking of EXTs by these three PRXs in plant cells.We hypothesize that absent or low O-glycosylated form of EXT were developed in this work  . Paramethis work . The EXTeviously . The tot systems , which aT chains . Both exO-glycosylated EXTs have severe defects in root hair growth [O-glycosylated species. In addition, O-glycosylated EXT variants docked in a rather dispersed way, while non-O-glycosylated variants preferentially docked in a grooved area , with a second Tyr a few Angstroms away. The arrangement and distances between the Tyr residues suggest that this could be an active site where Tyr crosslinking takes place. Although it is not possible to compare the interaction energies obtained with the different EXT species among docking runs, a general trend can be observed in O-glycosylated EXT variants. When we compared interaction energies among different PRXs interacting with EXT substrates with the same degree of O-glycosylation, we observed that PRX73 displayed the highest interaction activity with the non-hydroxylated EXT species. PRX44 displayed the highest interaction energy with the O-glycosylated species. Altogether, these results are consistent with the constitutive root hair growth effect observed for 35S:PRX44 and 35S:PRX73 and with non-glycosylated EXT being the substrate of peroxidation. Overall, this possibly indicates that PRX44 and PRX73 might interact with EXT substrates and possibly catalyze Tyr crosslinking in open regions of the EXT backbones with little or no O-glycosylation. This is in agreement with previous studies that suggested that high levels of O-glycosylation in certain EXT segments physically restrict EXT lateral alignments, possibly by acting as a branching point [To test if these three PRXs  might be able to interact with single-chain EXTs, we performed homology modeling with GvEP1, an EXT-PRX that is able to crosslink EXTs in in vitro conditions ,43, and r growth . Our docved area . Furtherng point ,7,51.A. thaliana PRX have been identified in available Brassicaceae genomes and in various Angiosperm and Gymnosperm families, but not in Lycophytes and Bryophytes. Thus, these three PRX sequences were the result of ancestral duplications before the divergence of Gymnosperms and Angiosperms but after the emergence of the Tracheophytes , the other two Arabidopsis PRX sequences did not cluster with any other predicted EXT-PRXs, such as PRX09 and PRX40 . Indeed, the other known EXT-PRXs (identified mostly based on in vitro evidence) did not cluster together, but were widely distributed in the tree  may have evolved together as a protein cluster, we performed comprehensive phylogenetic analyses of class-III peroxidases across diverse land plant lineages. Under low selective pressure, to maintain substrate specificity, EXT-PRX activities might have evolved multiple times during land plant evolution through gene duplication followed by neofunctionalization or subfunctionalization. PRX01, PRX44, and PRX73 belong to three independent orthologous groups , and orteophytes . Ortholoeophytes . This stthe tree . This an2O2 consumption and affecting the cell wall hardening process. In these polar growing cells, it is known that H2O2 is primarily derived from the respiratory burst oxidase homolog C (RBOHC) and, to a lower extent, from RBOHH and RBOHJ activities that produce superoxide ions [2O2. Then, part of H2O2 might be transported from the apoplast to the cytoplasm side by specific PIPs, as it was shown in other plant cell types , in response to diverse stimuli [prx01,44,73, high levels of H2O2 accumulate in the apoplast, triggering cell wall loosening through the oxidative cycle (OC). This affects growth homeostasis and inhibits expansion by decreasing root hair growth and cell wall thickness  caused root hair bursting [apoROS modulates cell growth by impacting cell wall properties. Our results suggest that either low or high levels of apoplastic class-III PRXs in the root hair cell walls affect ROS homeostasis and cell wall assembly, with a detrimental effect on cell expansion. Changes in ROS homeostasis produced by altered levels of these apoplastic PRXs might affect the secretion, targeting, and possibly the crosslinking of cell wall components, including EXTs, affecting root hair elongation [Based on the results shown in this work, we propose a working model in which PRX01, PRX44, and PRX73 (and possibly other PRXs) control root hair growth at room temperature by channeling Hide ions ,55,56 th stimuli ,46,47. Whickness . Concomibursting , reinforongation .Arabidopsis thaliana have no assigned biological function. In this work, we have characterized three related EXT-PRXs, PRX01, PRX44, and PRX73, that function in ROS homeostasis and potentially in EXT assembly during root hair growth. These PRXs might control Tyr crosslinking in EXTs and related O-glycoproteins and modify its secretion and assembly in the nascent tip cell walls. Using modeling and docking approaches, we were able to measure the in silico interactions of these PRXs with single-chain EXT substrates. The O-glycosylation levels in the EXT peptides clearly modified the interactions with these PRXs. PROLYL 4-HYDROXYLASE (P4H5), PEPTIDYL-SER GALACTOSYLTRANSFERASE (SGT1/SERGT1), and REDUCE RESIDUAL ARABINOSE 3 (RRA3) are key enzymes that modify EXT hydroxylation (P4H5) and EXT O-glycosylation (SERGT1 and RRA3) [4H5 is a 2-oxoglutarate (2OG) dioxygenase that catalyzes the formation of trans-4-hydroxyproline (Hyp/O) from peptidyl-proline preferentially in an EXT context, allowing these proteins to be O-glycosylated [l-arabinofuranose) attached to the Hyp in the EXT peptides. SERGT1 add the single galactose units to the serine in the repetitive motif of Ser-(Pro)3–5 present in EXT and EXT-related proteins . All these lines of evidence indicate that PRX01, PRX44, and PRX73 are important enzymes that could be involved in the O-glycosylated EXT assembly during root hair growth. Similarly, we recently characterized PRX62 and PRX69 as key apoplastic PRXs that modulate ROS homeostasis and cell wall EXT insolubilization linked to root hair elongation at low temperature [Currently, most of the 73 apoplastic class-III PRXs in nd RRA3) . Specifiosylated ,18. In tosylated ,58, theyperature . Collectperature ,60. Whilperature , EXT assperature ,20,51. TArabidopsis thaliana Columbia-0 (Col-0) was used as the wild-class (Wt) genotype in all experiments. All mutants and transgenic lines tested are in this genetic background. Seedlings were germinated on agar plates in a Percival incubator at 22 °C in a growth room for 7 days at 140 μmol m−2 s−1 light intensity. Plants were transferred to soil for growth under the same conditions. For identification of T-DNA knockout lines, genomic DNA was extracted from rosette leaves. Confirmation by PCR of a single and multiple T-DNA insertions in the target PRX genes was performed using an insertion-specific LBb1.3 primer in addition to one gene-specific primer. To ensure gene disruptions, PCR was also run using two gene-specific primers, expecting bands corresponding to fragments larger than in WT. We isolated homozygous lines for PRX01 , PRX44 , and PRX73 . SERGT1 (sergt1-1 SALK_054682), rra3 (GABI_233B05) [p4h5 T-DNA mutant [_233B05) , and p4hA mutant  were isoVectors based on the Gateway cloning technology (Invitrogen) were used for all manipulations. Constitutive expression of PRXs-GFP-tagged lines were achieved in plant destination vector pMDC83. cDNA PRXs sequences were PCR-amplified with AttB recombination sites. PCR products were then recombined first in pDONR207 and transferred into pGWB83. To generate transcriptional reporter, the PRX promoter regions (2 Kb) were amplified and recombined first in pDONR207 and transferred into pMDC111. All the transgenic lines used in this study are described in The binary vector pART27, encoding tdTomato (TOM), secreted with the secretory signal sequence from tomato polygalacturonase, and expressed by the constitutive CaMV 35S promoter (pART-SS-TOM), was the kind gift of Dr. Jocelyn Rose, Cornell University. The entire reporter protein construct was excised from pART-SS-TOM by digesting with NotI. The resulting fragments were gel-purified with the QIAquick Gel Extraction Kit and ligated using T4 DNA Ligase (New England Biolabs) into dephosphorylated pBlueScript KS+ that had also been digested with NotI and gel-purified to make pBS-SS-TOM. The plasmid was confirmed by sequencing with primers 35S-FP (5′-CCTTCGCAAGACCCTTCCTC-3′) and OCS-RP (5′-CGTGCACAACAGAATTGAAAGC-3′). The sequence of the EXT domain from SlPEX1 (NCBI accession AF159296) was synthesized and cloned by GenScript into pUC57 (pUC57-EXT). The plasmid pBS-SS-TOM-EXT-LONG was made by digesting pUC57-EXT and pBS-SS-TOM with NdeI and SgrAI, followed by gel purification of the 2243 bp band from pUC57-EXT and the 5545 bp band from pBS-SS-TOM, and ligation of the two gel-purified fragments. The pBS-SS-TOM-EXT-LONG plasmid was confirmed by sequencing with 35S-FP, OCS-RP, and tdt-seq-FP (5′-CCCGTTCAATTGCCTGGT-3′). Both pBS plasmids were also confirmed by digestion. The binary vector pART-SS-TOM-EXT-LONG was made by gel purifying the NotI insert fragment from the pBS-SS-TOM-Long EXT plasmid and ligating it with pART-SS-TOM backbone that had been digested with NotI, gel purified, and dephosphorylated. This plasmid was confirmed by sequencing. The construct SS-TOM and SS-TOM-Long-EXT were transformed into Arabidopsis plants. The secretory sequence (SS) from tomato polygalacturonase is MVIQRNSILLLIIIFASSISTCRSGT (2.8 kDa) and the EXT-Long domain sequence with six alanine cluster is BAAAAAAACTLPSLKNFTFSKNIFESMDETCRPSESKQVKIDGNENCLGGRSEQRTEKECFPVVSKPVDCSKGHCGVSREGQSPKDPPKTVTPPKPSTPTTPKPNPSPPPPKTLPPPPKTSPPPPVHSPPPPPVASPPPPVHSPPPPVASPPPPVHSPPPPPVASPPPPVHSPPPPVASPPPPVHSPPPPVHSPPPPVASPPPPVHSPPPPVHSPPPPVHSPPPPVHSPPPPVHSPPPPVASPPPPVHSPPPPVHSPPPPVHSPPPPVASPPPPVHSPPPPPPVASPPPPVHSPPPPVASPPPPVHSPPPPVASPPPPVHSPPPPVHSPPPPVHSPPPPVASPPPALVFSPPPPVHSPPPPAPVMSPPPPTFEDALPPTLGSLYASPPPPIFQGY × 395-(39.9 kDa). The predicted molecular size for SS-TOM protein is 54.2 kDa and for SS-TOM-EXT-Long Mw is 97.4 kDa. All the transgenic lines used in this study are described in prx01,44,73 mutant, 35S:PRX-GFP lines, and Wt Col-0, 200 fully elongated root hairs were measured (n roots = 20–30) from seedlings grown on vertical plates for 10 days. Values are reported as the mean ±SD using the Image J software. Measurements were made after 7 days. Images were captured with an Olympus SZX7 Zoom microscope equipped with a Q-Colors digital camera.For quantitative analysis of root hair phenotypes in Root hairs were ratio imaged with the Zeiss LSM 710 laser scanning confocal microscope  using a 40× oil-immersion, 1.2 numerical aperture. EGFP (473–505 nm) emission was collected using a 458-nm primary dichroic mirror and the meta-detector of the microscope. Bright-field images were acquired simultaneously using the transmission detector of the microscope. Fluorescence intensity was measured in 7 µm region of interest (ROI) at the root hair apex. For the lines SS-TOMATO and SS-TOMATO-EXT-LONG in the different genetic backgrounds, roots were plasmolyzed with an 8% mannitol solution and the scanning was performed using Zeiss LSM 510 META  . The GFP signal and TOM cell wall signal at the RH tip were quantified using the ImageJ software. Fluorescence AU were expressed as the mean ± SD using the GraphPad Prism 8.0.1  statistical analysis software. Results are representative of two independent experiments, each involving 10 roots, and approximately between 10 and 20 hairs per root were observed.−2 s−1 light intensity by grinding in 20 mM HEPES, pH 7.0, containing 1 mM EGTA, 10 mM ascorbic acid, and PVP PolyclarAT . The extract was centrifuged twice for 10 min at 10,000 g. Each extract was assayed for protein levels with the Bio-Rad assay . PRX activity was measured at 25 °C by following the oxidation of 8 mM guaiacol  at 470 nm in the presence of 2 mM H2O2  in a phosphate buffer . Values are the mean of three replicates ± SD.Soluble proteins were extracted from roots grown on agar plates in a Percival incubator at 22 °C in a growth room for 7 days at 140 μmol m2DCF-DA) is used as a cell-permeable fluorogenic probe to quantify reactive oxygen species (ROS). H2DCFDA diffuses into cells and is deacetylated by cellular esterases to form 2′,7′-dichlorodihydrofluorescein (H2DCF). In the presence of ROS, predominantly H2O2, H2DCF is rapidly oxidized to 2′,7′-dichlorofluorescein (DCF), which is highly fluorescent, with excitation and emission wavelengths of 498 and 522 nm, respectively. To measure cytoplasmic ROS in root hair cells, growth of Arabidopsis seeds on a plate was conducted with 1% sterile agar for 7 days in a chamber at 22 °C with continuous light. These seedlings were incubated in darkness on a slide for 10 min with 50 μM H2DCFDA at room temperature. Samples were observed with Zeiss Imager A2 Epifluorescence. A 10× objective was used, 0.30 N.A., and exposure time 80–500 ms. Images were analyzed using ImageJ 1.50 b software. To measure ROS mean, a circular region of interest (ROI) (r = 2.5) was chosen in the tip zone of the root hair. All root hairs of six seedlings per genotype were analyzed. The reported values are the mean ± standard deviation (mean ± SD).2′,7′-dichlorodihydrofluorescein diacetate  for 20 min in dark conditions and rinsed with liquid MS. Root hairs were imaged with a Zeiss LSM5 Pascal laser scanning confocal microscope. The fluorescence emission of oxidized AUR in the apoplast of root hair cells was observed between 585 and 610 nm using 543 nm argon laser excitation, 40× objective, N/A = 1.2. The intensity of fluorescence was quantified on digital images using ImageJ software. Quantification of the AUR probing fluorescence signal was restricted to apoplastic spaces at the root hair tip. The measurements were performed in three independent experiments (n ≥ 5) with the same microscopic settings.Zinnia elegans, and 4 putative extensin class-III PRXs from Lupinus album, Lycopersicum esculentum, Phaseolus vulgaris, and Vitis vinifera have been aligned with ClustalW and the tree constructed using the neighbor-joining method [http://peroxibase.toulouse.inra.fr) Accessed on 1 March 2022 [A total of 73 class-III PRX protein sequences from A. thaliana, 2 putative lignin class-III PRXs from g method . The anag method . All prorch 2022 .http://aranet.mpimp-golm.mpg.de) Accessed on 1 March 2022 and trimmed to facilitate readability . Each co-expression of interest was confirmed independently using the expression angler tool from Botany Array Resource BAR (http://bar.utoronto.ca/ntools/cgi-bin/ntools_expression_angler.cgi) Accessed on 1 February 2018 and ATTED-II (http://atted.jp). Accessed on 1 February 2018 Only those genes that are connected with genes of interest are included.Co-expression networks for RSL4 root hair genes were identified from PlaNet  with 10 mM phenol . Hydrolysates were dried under a steady stream of nitrogen (gas) and then redissolved at 10 mg ml-1 in water. The hydrolysates were fractionated by gel permeation chromatography on a polyhydroxyethyl A column  equilibrated in 50 mM formic acid and eluted isocratically at a flow rate of 0.8 mL min−1. UV absorbance was monitored at 280 nm. The amounts of Tyr and IDT in the hydrolysates were then determined by comparison with peak areas of authentic Tyr and IDT standards. Response factors were determined from three level calibrations with the Tyr and IDT standards.Alcohol-insoluble residues of root tissues obtained from w/v) SDS, 10% (v/v) glycerol, 6 M UREA, 1% (v/v) β-mercaptoethanol, 1 mM PMSF). Samples were immediately transferred to ice. After centrifugations at 13000 rpm at 4 °C for 20 min, supernatant was moved to a new 1.5 mL tube and equal volumes of Laemmli buffer  SDS, 40% (v/v) glycerol, 10% (v/v) β-mercaptoethanol, 0.002% (w/v) bromophenol blue) were added. The samples (0.5–1.0 mg/mL of protein) were boiled for 5 min and 30 μL were loaded on 10% SDS-PAGE. The proteins were separated by electrophoresis and transferred to nitrocellulose membranes. Anti-GFP mouse IgG  was used at a dilution of 1:2000 and it was visualized by incubation with goat anti-mouse IgG secondary antibodies conjugated to horseradish peroxidase (1:2000), followed by a chemiluminescence reaction . For the SS-TOM lines analysis, proteins were extracted in 2× SDS buffer ), using 10 μL of buffer per mg of plant tissues of Wt Col-0, transgenic lines 35S:SS-TOM, and 35S:SS-TOM-EXT-LONG. Two transgenic lines were analyzed. A total of 10 μL of supernatant of each protein extract was run into a 12% polyacrylamide gel during one hour at 200 V, and then transferred to a PVDF membrane. PVDF was blocked with 5% milk in TBST  for 1 h at 4 °C, and then washed four times during 15 min in TBST. An anti-RFP  was used as the primary antibody (that recognizes TOM protein) overnight at 4 °C. After four washes of 15 min each in TBST at room temperature, it was incubated two hours with a secondary antibody anti-rabbit (goat) conjugated with alkaline phosphatase  in a 1:2500 dilution with TBST. This was followed by four washes of 15 min each in TBST at room temperature. Finally, 10 μL of alkaline phosphatase  containing 80 μL NBT  (35 mg/mL in 70% DMSO) and 30 μL de BCIP (Sigma) (50 mg/mL in 100% de DMSO) was used.Plant material (100 mg of root from 15-day-old seedlings grown as indicated before) was collected in a microfuge tube and ground in liquid nitrogen with 400 μL of protein extraction buffer . Polymerization was performed at 60 °C. Sections were stained with 2% uranyl acetate in 70% methanol, followed by Reynold’s lead citrate (2.6% lead nitrate and 3.5% sodium citrate (pH 12.0)) and observed in a Tecnai 12 electron microscope. Quantitative analysis of cell wall thickness was performed using FIJI.Seeds were germinated on 0.2× MS, 1% sucrose, 0.8% agar. Seven days after germination, seedlings were transferred to new 0.2× MS, 1% sucrose, 0.8% agar plates. After 4 additional days, 1-mm root segments with root hairs were fixed in 2% glutaraldehyde in 0.1 M cacodylate buffer pH 7.4. Samples were rinsed in cacodylate buffer and post-fixed in 2% OsOVitis vinifera peroxidase 24, GvEP1, LOC100254434). Homology modeling was performed for all PRXs using modeller 9.14 [https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5045529/ Accessed on 1 February 2020. Ligand starting structure was generated as the most stable structure by molecular dynamics [Modeling and molecular docking: cDNA sequences of PRXs were retrieved from TAIR  and NCBI Nucleotide DB  and Parrinello–Rahman barostat [The use of coarse-grained (CG) molecular dynamics (MD) allowed collection of long timescale trajectories. System reduction is significant when compared to all atom models, approximately reducing on order of magnitude in particle number. In addition, a longer integration time step can be used. Protein residues and coarse-grained solvent parameters correspond to the SIRAH model , while abarostat , and a 1barostat  and visubarostat . Volume barostat , and ave


Overweight and obesity are defined by an anomalous or excessive fat accumulation that may compromise health. To find single-nucleotide polymorphisms (SNPs) influencing metabolic phenotypes associated with the obesity state, we analyze multiple anthropometric and clinical parameters in a cohort of 790 healthy volunteers and study potential associations with 48 manually curated SNPs, in metabolic genes functionally associated with the mechanistic target of rapamycin (mTOR) pathway.FNIP2 mRNA levels in cancer cell lines and in peripheral blood from carriers of the C allele. Because the miRNA binding site is conserved across vertebrates, we engineered the T-to-C substitution in the endogenous Fnip2 allele in mice. Primary cells derived from Fnip2 C/C mice show increased mRNA stability, and more importantly, Fnip2 C/C mice replicate the decreased adiposity and increased leanness observed in human volunteers. Finally, expression levels of FNIP2 in both human samples and mice negatively associate with leanness parameters, and moreover, are the most important contributor in a multifactorial model of body mass index prediction.We identify and validate rs2291007 within a conserved region in the 3′UTR of folliculin-interacting protein FNIP2 that correlates with multiple leanness parameters. The T-to-C variant represents the major allele in Europeans and disrupts an ancestral target sequence of the miRNA miR-181b-5p, thus resulting in increased FNIP2 mRNA levels.We propose that rs2291007 influences human leanness through an evolutionarily conserved modulation of The online version contains supplementary material available at 10.1186/s13059-022-02798-5. Moreover, an elevated BMI strongly associates with several metabolic abnormalities, including insulin resistance and metabolic syndrome, themselves prominent risk factors for type 2 diabetes (T2D), cardiovascular diseases (CVDs) [Overweight and obesity are caused by an excessive and anomalous accumulation of adipose tissue and constitute a risk to health . Accordis (CVDs) . In addis (CVDs) .FTO), the first genetic determinant of human body mass [Genetic Investigation of ANthropometric Traits consortium (GIANT) meta-analysis  linked a total of 97 loci with BMI, 56 of which were novel. The 97 loci account for 2.7% of BMI variation, and genome-wide studies estimate that common variants account for more than 20% of BMI variation [Both genetic and environmental factors contribute to the development of overweight and obesity. Lifestyle habits such as excessive caloric intake and insufficient physical activity are critical drivers of overweight and obesity . In addiody mass , 9. A Geariation –12. ThusIt is not surprising that both genetic and environmental factors that contribute to obesity modulate cell signaling pathways responsive to nutrients and metabolic hormones. Among these pathways, the mechanistic target of rapamycin complex 1 (mTORC1) signaling pathway concurrently senses energy, nutrients, and growth factors and couples their sufficiency to the execution of anabolic cell growth and division . MTORC1 While several studies have found single-nucleotide polymorphisms (SNPs) within components of the mTORC1 pathway affecting cancer susceptibility –18, mirrFNIP2) that affects mRNA stability. Such associations were replicated in a novel knock-in mouse strain genetically tailored to express the human-specific single-nucleotide variant. Moreover, in addition to the genetic association, the levels of FNIP2 mRNA inversely correlate with anthropometric and clinical features of obesity. Thus, we propose that both rs2291007 and FNIP2 blood mRNA levels are linked to obesity.Here, we measured BMI and multiple anthropometric and clinical features related to obesity in a cohort of 790 healthy volunteers and analyzed potential associations with 48 manually curated SNPs in metabolic genes with known functional associations to the mTORC1 pathway. We found an association between multiple metabolic parameters related to obesity and a human-specific SNP within an evolutionarily conserved region of the 3′UTR of the folliculin-interacting protein 2  were associated with metabolic phenotypes . Among these SNPs, the two located in FNIP2 gene maintained statistical significance after applying the Bonferroni correction for multiple comparisons , Bonferroni-corrected p-value= 0.04 and rs2291007, beta=1.33, 95% CI (0.59–2.07), Bonferroni-corrected p-value= 0.03). rs2291007 was also associated with muscle mass , Bonferroni-corrected p-value=0.02) , located in 5′UTR, intronic, and 3′UTR regions, respectively  losing statistical significance in predictive models for fat mass adjusted by sex and age. In addition to the associations with fat and muscle mass, the minor allele T of rs2291007 positively associated with several metabolic phenotypes, including weight and visceral fatness ; p-value=0.001, Bonferroni-corrected p-value= 0.06 and beta= 0.5, 95% CI (0.2–0.81); p-value=0.001, Bonferroni-corrected p-value= 0.08 respectively). We also detected various association trends of rs2291007 with BMI, waist circumference, and hip circumference ; p-value=0.002, beta= 1.77, 95% CI (0.53–3); p-value=0.005 and beta= 1.28, 95% CI (0.04–2.51); p-value=0.04 respectively)  [https://sfold.wadsworth.org/cgi-bin/index.pl) [According to TargetScanHuman predictions ert_72/) , the seq/ , the sndex.pl)   cell lines [FNIP2, as compared to cells carrying at least one copy of the C allele (77.8%)  Fig. A, consisFNIP2 expression in carriers of the rs2291007 T allele by analyzing peripheral blood mononuclear cells (PBMC) of 161 healthy volunteers. Indeed, we found that homozygous TT individuals (25.46%) also showed lower FNIP2 expression  than individuals carrying at least one C allele (74.54%). When adjusted to sex and age, the associated p-value increased  , while no trend was observed in carriers homozygous for the C allele   and diastolic (DBP) blood pressure, blood levels of triglycerides and glycated hemoglobin, and low basal metabolism, and with increased muscle mass, all with high statistically significant p-values  Fig. B. We alsFNIP1 and FLCN. FNIP2 gene expression significantly correlated with both FNIP1 and FLCN  and quantified the levels of Fnip2 mRNA in complete culture medium and in medium without amino acids to modulate the expression of Fnip2. Although we observed the expected increase in Fnip2 mRNA levels upon amino acid deprivation, there was no difference between the levels of Fnip2 mRNA in Fnip2T/T and Fnip2C/C MEFs  was observed  in samples from Fnip2C/C versus Fnip2T/T livers and WAT. Strikingly, among the top 5 signatures identified in both liver and WAT analyses, “adipogenesis,” “fatty acid metabolism,” and “mTORC1 signaling” were enriched samples from of Fnip2T/T mice , plus sex and age. Importantly, the inclusion of a FNIP2*rs2291007 interaction was significant and increased the optimism-corrected R2, so it was accepted in the final model. Figure FNIP2 expression associates with a decreased BMI , p-value= 2.12×10−15). Conversely, the beta parameter for the FNIP2*rs2291007 interaction is positive , p-value= 0.03), which means that the inclusion of a T variant results in a significantly less negative slope, and thus to a less dramatic decrease of BMI with higher FNIP2 expression values. The inclusion of miR181-5p expression did not result in an improved model nor did the interactions between gender and rs2291007 (gender*rs2291007) or between gender and FNIP2 gene expression (gender*FNIP2), neither the use of a codominant or dominant assumption for the SNP.Overweight and obesity are complex conditions modulated by several causes, so we designed a multifactorial model to predict BMI taking into consideration the relevance of genetic susceptibility of the FLCN-FNIP complex investigated herein. We derived a linear regression model that included the rs2291007 SNP (in additive form), three gene expression variables  but none related to BMI or metabolic alterations (https://www.ebi.ac.uk/gwas/genes/FNIP2). Notably, germ-line mutations in other members of the folliculin complex, FLCN gene, are associated with Birt-Hogg-Dube syndrome, which is characterized by fibrofolliculomas, renal tumors, lung cysts, and pneumothorax [FNIP2 gene is associated with metabolic and obesity-related phenotypes  and with decreased muscle mass in healthy European individuals  of IMDEA-Food Institute. Among them, RNA from 161 volunteers was used for gene expression analysis and microRNA studies were performed in 89 individuals. Volunteers, aged between 18 and 72 years, were recruited during the period 2012–2018 and did not suffer from any serious diseases. All contributors signed the consent participation form. These studies were approved by the IMDEA Food Research Ethics Committee and methodologies conformed to the standards set by the Declaration of Helsinki.2). The World Health Organization’s criteria (WHO) was employed to catalog the volunteers as normal weight when BMI < 25 kg/m2 and as overweight when BMI ≥ 25 kg/m2. Waist and hip circumference were measured with a flexible Dry 201 metal tape, with measuring range 0–150 cm and 1 mm of precision . Blood sample extractions, biochemical determinations (lipid and glycemic profiles), and nutritional assessments  were collected following an overnight fasting as previously described [Relevant phenotypic information is summarized in Additional file escribed –44.https://www.ncbi.nlm.nih.gov/snp/), Ensembl (http://www.ensembl.org/index.html), and GWAS catalog (https://www.ebi.ac.uk/gwas/). Fifty-six SNPs in 25 genes of the mTOR pathway . Genotyping was performed with QuantStudio 12 K Flex Real-Time PCR System  using TaqMan OpenArray plates following the manufacturer’s instructions and results were analyzed using TaqMan Genotyper software.http://www.targetscan.org/vert_72/) for prediction of microRNA targets [https://sfold.wadsworth.org/cgi-bin/index.pl) for statistical folding of nucleic acids and studies of regulatory RNAs [Two in silico tools were used for predicting miR181 structure and binding to rs2291007 region: TargetScanHuman . HEK-293T cells were transfected using Lipofectamine 2000  according to the manufacturer’s recommendations. Each reaction contained 100 ng of either psiCheck2-3′UTR-FNIP2-rs2291007-C or psiCheck2-3′UTR-FNIP2-rs2291007-T and 30 nM of miR181b mimic miRNA  [FNIP2 upon binding to their 3′UTR of miR181b.Sequences for MA, USA) . RelativFNIP2 (Hs01574322_m1), FLCN (Hs00376065_m1), FNIP1 (Hs00382846_m1), GAPDH (Hs02786624_g1). The 2−ΔΔCt method was applied to calculate the relative gene expression. COSMIC Cell Lines Project (https://cancer.sanger.ac.uk/cell_lines) was used to download genotypes and gene expression values for FNIP2 in 965 cell lines.For human peripheral blood samples, we used TRIzol method or RNeasy Mini Kit  following the manufacturer’s conditions to obtain total RNA. Reverse transcription was performed with the High-Capacity cDNA Reverse Transcription kit , following the manufacturer’s instructions. RT-PCR reactions were performed as previously described  using Qu−ΔΔCt method was applied to calculate the relative gene expression, using β-actin as reference gene.For mouse tissues and primary cells, RNA was extracted using TRIzol together with RNeasy Mini Kit  or Direct-zol RNA Miniprep . Reverse transcription was performed using SuperScript IV VILO Master Mix . Quantitative real-time PCR was run in triplicates using GoTaq qPCR Master Mix  in a QuantStudio 6 Flex Real-Time PCR System thermocycler (Applied Biosystems). The 2Total RNA obtained from human peripheral blood samples and from mouse primary cells was retrotranscribed using TaqMan microRNA reverse transcription kit . Real-time PCR was run in triplicates using TaqMan Fast Advanced Master Mix  with specific TaqMan probes: hsa-miR-181b , U6 snRNA , mmu-miR-181b-5p , and snoRNA202 .Fnip2 rs2299007 C allele in mice, C57BL/6 mouse blastocysts were injected with Cas9, a single-guide (sg) RNA targeting the sequence of interest and a repair single-stranded oligonucleotide containing the intended mutations flanked by 70 bp of homology arms adjacent to the double-strand break site. Genotyping was performed by specific amplification followed by restriction fragment length polymorphism (RFLP) and/or Sanger sequencing.To engineer sgRNA: GATAAGTGATATGAATGTATRepair single-stranded oligonucleotide:CCGAGCAGAAGTGTCTCAGTGTCCTGTAATGACCTCTTCTAGCATGTTGCAGTTTTATATTTGTTAAGTTGATAAGTGATATGAACGTATACGCAATTGTGTATGTTTTCAAAAAGGACAATGAAAATTTAAAATGTAGCTTCCACACTTGTGCATAATTCCAAll animal procedures carried out at the CNIO were performed according to protocols approved by the CNIO-ISCIII Ethics Committee for Research and Animal Welfare (CEIyBA), under protocol number PROEX 015/18. Mice were housed under specific pathogen-free (SPF) conditions, at 22 °C and with 12-h dark/light cycles. Mice were fed with a standard chow diet (Harlan Teklad 2018). For fasting experiments, mice were placed in clean cages without access to food from 4 pm to 8 am.For densitometry analysis, body composition  was measured using dual-energy X-ray absorptiometry (DEXA) PIXImus, Mouse Densitometer , software version 1.46. During the measurements, mice were anesthetized with isoflurane. Quality control was performed using a calibrated phantom before imaging.MEFs were isolated from E13.5 embryos using a protocol consisting of a chemical digestion with trypsin followed by mechanical disaggregation. For amino acid starvation experiments, cells were rinsed 3 times and placed in RPMI medium without amino acids  supplemented with 10% dialyzed serum. Amino acid stimulation was performed adding a cocktail containing the 20 amino acids (with concentration as in RPMI) directly to cell culture plates.Cells were rinsed once with ice-cold PBS and lysed in ice-cold protein lysis buffer containing 50 mM HEPES (pH 7.4), 40 mM NaCl, 2 mM EDTA, 1.5 mM sodium orthovanadate, 50 mM NaF, 10 mM pyrophosphate, 10 mM glycerophosphate, and 1% Triton X-100 and one tablet of complete protease inhibitors (Roche) per 25 ml. Cell lysates were cleared by centrifugation at maximum speed for 10 min. Protein content was measured from extracts with BCA Protein Assay. Protein extracts were denatured by adding sample buffer and boiling for 5 min, resolved by SDS-PAGE and analyzed by immunoblotting. Western blot analyses were performed according to standard procedures. Results were visualized using Odyssey Infrared Imaging System LI-COR Biosciences. The following primary antibodies were used: P-T389-S6K , S6K , TFEB , and β-actin .For mRNA stability measurements MEFs were treated with 5 μg/mL Actinomycin D for 2 and 4 h to stop transcription. RNA was extracted using Direct-zol RNA Miniprep .t test, or through linear models with adjustment variables. SNPs were categorized by genotype . Deviations from Hardy-Weinberg equilibrium of genotype frequencies at individual loci were assessed using standard χ2 tests. Linkage disequilibrium was quantified through the r2 and D’ statistics.Descriptive analysis was implemented for different continuous and categorical variables. Associations between gene expression variables were analyzed through Pearson correlation coefficients and tested through the corresponding test. Differences between gene expression in two groups were tested through Student’s Associations of the SNPs with numerical variables were modeled through linear regression on the SNP adjusted by sex and age. Associations with binary variables were modeled through logistic regression adjusted by sex and age. An additive model for the SNPs  was considered by default, as in general it gave better fits, although in some cases a recessive or dominant model was considered.R2, MSE or Mean Square Error) by optimism in order to assess its predictive power and possible overfit.A final multifactorial model to predict BMI was validated through bootstrap, using 2000 bootstrap samples, which allowed to correct the performance statistics  of the corresponding variables.This final model was obtained by sequentially adding SNP and gene expression variables to a basal model with only sex and age as predictor variables. A new variable was accepted if it was statistically significant and in addition produced a new model with an increased optimism-corrected p-values. All statistical analyses were performed using the R statistical software, version 3.6.1 (www.r-project.org).All tests were bilateral, with a significance level of 0.05. Ninety-five percent confidence intervals (95% CI) were used in parameter estimates (betas and odds ratios). Bonferroni method was applied for multiple-test correction of the t test was used for single comparisons. Associations between gene expression levels and body weight were modeled using a simple linear regression.Statistical analyses were carried out with Prism 8 (GraphPad). Experiments including a second variable  were analyzed using 2-way ANOVA with Sidak’s multiple comparison post-test. Where appropriate, the area under the curve (AUC) was calculated. Unpaired Student’s Fnip2C Knock-in mouse to model FNIP2 rs2291007. Figure S5 . Table S2. List of SNPs, genes, location, type, and minor allele frequencies genotyped in this study. Table S3. Detailed information of SNPs associations with metabolic characteristics. Table S4. Associations of FNIP2, FNIP1, FLCN and miR-181b expression with metabolic phenotypes.Additional file 3. Review history.


PD-1+CD8+ T cell frequency was also negatively correlated with CCR5 and HLA-DR expression on CD4+ T cells and predicted stronger HIV-specific T lymphocyte responses. In the CD8+ T cell compartment of PSPs, we identified an enrichment of stem-like TCF-1+PD-1+ memory cells, whereas pediatric progressors and viremic adults had a terminally exhausted PD-1+CD39+ population. TCF-1+PD-1+ expression on CD8+ T cells was associated with higher proliferative activity and stronger Gag-specific effector functionality. These data prompted the hypothesis that the proliferative burst potential of stem-like HIV-specific cytotoxic cells could be exploited in therapeutic strategies to boost the antiviral response and facilitate remission in infants who received early ART with a preserved and nonexhausted T cell compartment.HIV nonprogression despite persistent viremia is rare among adults who are naive to antiretroviral therapy (ART) but relatively common among ART-naive children. Previous studies indicate that ART-naive pediatric slow progressors (PSPs) adopt immune evasion strategies similar to those described in natural hosts of SIV. However, the mechanisms underlying this immunophenotype are not well understood. In a cohort of early-treated infants who underwent analytical treatment interruption (ATI) after 12 months of ART, expression of PD-1 on CD8 In cont viremia . Pediatr viremia –9. Both IV hosts , 10, 11 ph nodes , 13. How+CD8+ T cells expressing the transcription factor TCF-1 have been recognized by their memory and proliferative potential as capable of generating effector cells in the context of chronic antigen load in murine   who unde+ T cell percentage of 20% or less at younger than 18 months of age or less than 15% at older than 18 months of age. All participants were virologically suppressed, and CD4+ T cell counts were above 20% prior to ATI  and underwent ATI after 12 months on ART. ART was restarted after ATI according to the national South African and WHO guidelines prevailing at the time of the study : clinicar to ATI . Viral rr to ATI , but ther to ATI .+ T cells negatively correlated with time to restart therapy while unexpectedly, PD-1 expression on all CD8+ T cell subsets was positively correlated with slow progression (https://doi.org/10.1172/jci.insight.156049DS1). In the Least Absolute Shrinkage and Selection Operator (LASSO) model, where the duration of viral suppression during the first year, age at ART initiation, and CD4+ T cell counts were also included, PD-1 expression on effector memory CD8+ T cells was the primary variable selected and associated with slow progression.To identify parameters measured prior to ATI that predict immunological progression during ATI, we analyzed cryopreserved PBMCs collected during viral suppression at the time point immediately before ATI for the expression of activation and exhaustion markers on the T cell compartment. HLA-DR expression on central memory and terminal effector memory CD4+ T cells, was associated with lower CCR5+ and HLA-DR+ on total and central memory CD4+ T cells before ATI, two cardinal features previously identified in PSPs . Hi. Hi+ T c+ T cell population expressing PD-1, we looked at the coexpression of activation and exhaustion markers. PD-1+CD8+ T cells in the rapid progressors expressed more CD39 when compared with slow progressors . Although the transcriptomic analysis in sorted PD-1+CD8+ T cells from the time point immediately before ATI showed that a large proportion of differentially expressed genes appeared to be driven by individual heterogeneity (HAVCR2), a marker when coexpressed with PD-1+ that also characterizes terminally exhausted CD8+ T cells  3 months after ATI positively correlated with pre-ATI PD-1 expression on CD8+ T cells (P = 0.02) and negatively with pre-ATI HLA-DR+ expression on CD4+ T cells (P = 0.04)  . Similar+ T cell populations in a group of 182 ART-naive children, PD-1 was only positively associated with immune activation in children older than 5 years but not in the younger group ; however, their CD4antially . Both thntenance , 48. By + T cells in a group of older ART-naive PSPs  and pediatric progressors , matched by age and sex with a group of HIV-exposed uninfected children . Of note, none of the slow progressors described above were included in the older PSP group. A fourth group of horizontally infected ART-naive viremic adults  was included for comparison (+CD8+ T cells (excluding the naive subset) was higher in the HIV-infected groups (+ T cells were significantly lower in frequency in PSPs when compared with pediatric progressors (P = 0.002). The absolute levels of PD-1 expression measured by MFI were also higher in pediatric progressors and viremic adults when compared with HIV-exposed uninfected children (+PD-1+ nonnaive CD8+ T cells were increased in pediatric progressors (P = 0.003) and viremic adults (P < 0.0001) but not in PSPs when compared with HIV-exposed uninfected children (+PD-1+ on nonnaive CD8+ T cells in the pediatric groups (P < 0.0001) when viremic adults were compared with HIV-exposed uninfected children or with PSPs , while the long-lived TCF-1+ population relatively expanded  on HIV-specific CD8+ T cells. There was also a tendency for higher levels of CD39+ on antigen-specific CD8+ T cells in the viremic adults. As expected, the CD8+ T cell compartment in viremic adults was markedly populated with more differentiated subsets than in PSPs and pediatric progressors . These findings indicate an HIV-specific CTL population enriched with a stem-like phenotype in the PSP group. To test whether the constant TCR stimulation in viremic individuals affects the PD-1+TCF-1+ population, we stained cells from the same individuals with tetramers to identify CMV-pp65–specific CD8+ T cells. The frequency of PD-1+, CD39+, and TCF-1+ populations was lower in the CMV-specific CD8+ T cells than in the HIV-specific CD8+ T cells, and no differences were observed among the 3 groups  responses, there remains a minority of children/adolescents represented by the PSPs in whom the early childhood type of responses have persisted, with higher frequencies of the stem-like phenotype of PD-1–expressing CD8+ T cells observed.Immune responses alter from early life through childhood and adolescence into adulthood . Childreears old , whereasears old –9. It is+ T cell population expressing PD-1 and TCF-1 represents a promising target for T cell therapies because of the long-term survival and proliferative capacity of these stem-like cells. Superior viremic control in adult elite controllers is associated both with a stronger proliferative capacity of HIV-specific CTLs  consisted of horizontally infected ART-naive individuals with chronic infection matched by sex. The fourth group consisted of HIV-exposed uninfected children matched by age and sex. No data were available on viral load and drug suppression for the mothers of these children. In analyses done after ART initiation, samples were selected from the time point after 1 to 2 years of viral suppression.In addition, we investigated the immunophenotype of PD-1–expressing CD82. Then, cells were washed with PBS and stained with Live/Dead near-IR stain (Invitrogen) according to the manufacturer’s instructions. After incubation, cells were washed again and stained for 30 minutes at 4°C in FACS buffer containing the surface antibody mix. PBMCs were fixed and permeabilized with Cytofix/Cytoperm solution (BD Biosciences) for 45 minutes at 4°C and stained with the intracellular antibody mix) for 30 minutes at 4°C. Cells were washed and acquired on a BD Biosciences LSR II. The complete fluorochrome-conjugated antibody list is in Cryopreserved PBMCs were thawed and cells rested in R10 medium for 3 hours at 37°C in 5% COFour sets of peptide-HLA tetramers conjugated with BV421 were obtained from ImmunAware ApS: HLA-B*42:01/Gag-TL9 (TPQDLNTML), HLA-B*42:01/pp65-RV10 (RPHERNGFTV), HLA-B*81:01/Gag-TL9 (TPQDLNTML), and HLA-B*81:01/pp65-GL8 (GPISGHVL). Two million cryopreserved PBMCs were thawed and stained according to the manufacturer’s instructions. The subsequent staining protocol followed the description above. Samples were acquired on a BD Biosciences LSR II.+CD8+ T cells were sorted in triplicates using a FACSAria Fusion (BD Biosciences) directly into RLT buffer (Qiagen) containing 1% β-mercaptoethanol and stored at –80°C. RNA extraction, cDNA conversion, and whole-transcriptome-amplification were done using Smart-seq2 as previously described .The sequenced data were analyzed as follows: the sequences were demultiplexed using bcl2fastq snapshot 5  before alignment. FASTQs were aligned using the smartseq2 snapshot 8 workflows using “GRCh38_ens93filt” as the reference genome. Both protocols were adopted from the Cumulus workflow. The cell by gene matrix was subsequently loaded and analyzed using DESeq2 (v 1.2.8.1) in R. Samples with fewer than 9 million total reads and genes not found in more than 3 samples, or greater than a sum of 5 counts were excluded from further analysis. Differential gene expression was conducted using the Wald test. Gene set enrichment analysis (GSEA) was performed on genes pre-ranked based on the Wald statistic and analyzed via GSEA version 4.0.3 using the curated Hallmark gene set. Significant gene sets were filtered based on an adjusted + T cell epitope peptide list” compiled by Brander et al. in the Los Alamos database (https://www.hiv.lanl.gov).ELISPOT assays were performed contemporary to the PEHSS study in freshly isolated PBMCs and previously described and published . A confi2. Cells were washed with PBS and stained with CellTrace Violet (Life Technologies) for 10 minutes at room temperature. Cold FBS was used to quench the reaction, and labeled PBMCs were resuspended in R10 containing 10% human AB serum (Sigma-Aldrich). Next, 250,000 cells were plated in duplicate in 96-well round-bottom plates in the presence of anti-CD28/anti-CD49d at 1 μg/mL (BD Biosciences), HIV-Gag clade C, or CMV-pp65 pools of overlapping consensus peptides (NIH AIDS Reagent Program) at a final concentration of 2 μg/mL for each peptide. The negative control included DMSO in the same concentration of peptide pool solution and 2 μg/mL phytohemagglutinin L (Sigma-Aldrich) used as a positive control. Cells were incubated for 7 days at 37°C in 5% CO2 with a 20% top-up of media on day 4. Twelve hours before the end of incubation, the stimulation was boosted with the same concentration of the respective stimulus, and Brefeldin A at 5 μg/mL (BioLegend) and Monensin at 1 μg/mL (BioLegend) were added to allow the measurement of IFN-γ+ and TNF-α+ cells. Surface and intracellular staining followed as described.Cryopreserved PBMCs were thawed and rested overnight in R10 at 37°C in 5% COThe data were analyzed in FlowJo v10.6.2 (Tree Star LLC). Positive gates were selected using fluorescence minus one (FMO) and memory subsets were obtained using Boolean Gates. For proliferation and intracellular cytokine staining assays, positive responses were considered after subtracting the background if at least 3 times higher.corrplot package. When multiple covariates were identified in the correlation matrix, the LASSO model was built. LASSO (glmnet was used to obtain the optimal penalty via 10-fold cross-validation. For this study, a P value less than 0.05 was considered significant.Graphs were created and statistical analysis was done with GraphPad Prism v9.0.1 unless otherwise stated. Continuous variables are shown in median and IQR. Statistical comparison between 3 and 4 groups was done using a Kruskal-Wallis test followed by Dunn’s test to correct for multiple comparisons. A Wilcoxon matched-pairs test was performed for pairwise comparisons. Spearman’s test was used to show correlation and a simple linear regression model for best-fit line and 95% confidence interval. Memory subset distributions and pie charts were done with the permutation test performed by Spice version 6.0. The correlation matrix was built with the t. LASSO , 62 is aWritten informed consent was obtained from all participants prior to participation in the study, except those who were underage, where written informed consent was obtained from their mothers or caregivers. The study was approved by the University of KwaZulu-Natal Biomedical Research Ethics Committee, Durban, South Africa; the University of the Free State Ethics Committee, Bloemfontein, South Africa; and the Oxford Research Ethics Committee, Oxford, United Kingdom.VV and PG wrote the paper; contributed to the study conception and design; and contributed to the acquisition, analysis, and interpretation of the data. NL, EL, VR, AL, HNK, JGP, JG, JC, MML, and AG contributed to the study conception and design and analysis and interpretation of the data. EA, AS, RD, and CT contributed to the acquisition of the data; AG contributed to analysis and interpretation of the data; MM, JR, PK, AJP, GTW, KD, JF, BDW, PJ, and TN contributed to acquisition and interpretation of the data.