Table 2.
Summary of different human blood microbiota studies conducted on healthy or diseased individuals.
| Authors | Study Population | Sample | Study Design | Country | Methodology | Changes in Circulating Microbiota | Ref. |
|---|---|---|---|---|---|---|---|
| Healthy individuals | |||||||
| Nikkari et al., 2001 | 4 HI | Whole Blood | Cohort Study | USA | qPCR and rRNA targeting the conserved region of 16S rDNA by fluorescent probe | Bacteria from 5 divisions and 7 distinct phylogenetic groups detected in the blood. | [31] |
| McLaughlin et al., 2002 | 25 HI | Whole blood | Cohort Study | Canada | Characterization by 16S rRNA and gyrB genes Dark-field microscopy and FISH. | Pleomorphic antibiotic susceptible bacteria existing in healthy blood with limited growth a (possibly Pseudomonas). | [45] |
| Moriyama et al., 2008 | 2 HI | Whole Blood | Preliminary Study | Japan | 16S rRNA PCR and Sanger sequencing. | Aquabacterium, Budvicia, Stenotrophomonas, Serratia, Bacillus and Flavobacteria identified only in clones. | [41] |
| Damgaard et al., 2015 | 60 HI | Blood plasma and RBCs | Cross Sectional Study | Denmark | Blood samples incubated on TSA or blue lactose plates, 16S rRNA gene sequencing and colony PCR | Bacterial growth observed in 35% of RBC fractions and 53% of plasma fractions. Staphylococci, Propionibacterium, Micrococcus and Bacillus most frequently found. | [42] |
| Païssé et al., 2016 | 30 HI | Buffy Coat, Plasma and RBCs | Cohort Study | France | 16S rRNA gene qPCR and 16S targeted metagenomic sequencing (Illumina MiSeq) | All blood fractions were positive for bacterial DNA. Most prevalent Phyla were Proteobacteria, Actinobacteria, Firmicutes and Bacteroidetes | [30] |
| Panaiotov et al., 2021 | 28 HI | Whole blood, | Cohort Study | Bulgaria | 16S rRNA genes and ITS2 targeted sequencing on Illumina MiSeq and TEM. | Cultural and molecular characterization of healthy blood microbiota (Proteobacteria and Frimicutes were prominent) | [44] |
| Raeisi et al., 2022 | 50 HI | Whole blood | Cohort Study | Iran | 16S rRNA gene PCR pyro-sequencing | Cultures positive (12%) PCR positive (12%) Staphylococcus, Bacilli were main findings Direct blood PCR-sequencing: Bulkholderia | [43] |
| Diabetic vs. healthy Individuals | |||||||
| Amar et al., 2011 | 3280T2D | Leukocytes | Longitudinal cohort study | France | 16S rDNA quantitative PCR and Pooled pyrosequencing (V1-V2) | High 16S rDNA levels caused diabetes despite risk factors. Proteobacteria phylum represented the highest relative abundance (~90%). High prevalence of Ralstonia spp. in diabetes patients. | [46] |
| Qiu et al., 2019 | 150 (50 T2D 100 HI) | Blood plasma | Nested case-control study | China | 16S rRNA amplicon sequencing by Illumina MiSeq (V5-V6) | Aquabacterium, Pseudonocardia, and Xanthomonas genera and Bacteroides spp. showed an inverse while Alishewanella, Actinotalea, Pseudoclavibacter, Sediminibacterium spp. showed a positive correlation with diabetes. | [47] |
| Massier et al., 2020 | 75, (42 obese and 33 T2D) | Blood | Comparative Cohort study | Germany | 16S rRNA gene sequencing (V4-V5), CARD-FISH | Genus Lactobacillus, Acinetobacter and Lactococcus decreased in T2D while Tahibacter increased in T2D | [48] |
| Ghaemi et al., 2021 | 90(30 T2D, 30 Pre-D and 30 HI) | Buffy Coat | Cohort Study | Iran | Real-time PCR using genus-specific 16srRNA primers | Akkermansia, and Faecalibacterium were higher in HI compared to pre-diabetic and T2D | [49] |
| D’Aquila et al., 2021 | 1285 MARK-AGE Study | Whole blood | Cross-sectional Study | Selected European Countries | Quantification of 16S rRNA by Real-time qPCR (V3-V4) | High level of Bacterial DNA were associated with higher level of Insulin and glucose | [50] |
| Chakaroun et al., 2021 | 112(64 BO 24 T2D and 24 HI) | Whole Blood | Cohort Study | Germany | 16s rRNA sequencing (V4-V5) Bacteria were visualized by CARD-FISH | Loss of Bacillaceae and Bukholderiaceae in T2D and Anoxybacillus, Duganella, Acidibacter, Chryseomicrobium, Sphingomonas were decreased | [51] |
| Cardiovascular vs. Healthy Individuals | |||||||
| Amar et al., 2013 | 3936 CVD | Leukocytes | Longitudinal Study | France | Eubacteria and Proteobacteria 16S rDNA by qPCR | There was a positive correlation of Proteobacteria, and vice versa of Eubacteria, with cardiovascular events. | [36] |
| Rajendhran et al., 2013 | 41 (31 CVD 10 HI) | Whole blood | Comparative Case Study | India | Amplicon sequencing of 16S rDNA V3 region (Ion Torrent PGM) | Increase of Proteobacteria (Pseudomonadaceae and Gammaproteobacteria), decrease in Firmicutes (Staphylococcaceae) and Bacillales, in CVDs | [33] |
| Dinakaran et al., 2014 | 120(80 CVD 40 HI) | Blood plasma | Comparative quantitative study | India | 16S rDNA and β-globin gene concentrations by qRT-PCR. Shotgun and amplicon sequencing V3 region (Ion Torrent PGM) | The 16S rRNA/β-globin gene ratio was higher in CVDs patients than in controls Actinobacteria and Bacteriophages were dominant in CVDs patients whereas Proteobacteria and eukaryotic viruses were dominant in controls. | [35] |
| Amar et al., 2019 | 202 (99 CVD with MI 103 HRCVD) | Whole Blood | Case Control Study | France | 16S rRNA sequencing for V3–V4 regions | Norcardiaceae and Aerococcaceae families and Propionibacterium, Gordonia, Chryseobacterium, and Rhodococcus genera (cholesterol-degrading bacteria) were lower in patients with (vs. without) myocardial infarction. An increase in 16S rRNA gene concentration in CVDs. | [52] |
| Jing et al., 2021 | 300 (150 Hypertension and 150 HI) | Blood Plasma | Case Control Study | China | 16S rRNA gene (V6-V7) Miseq Illumina sequencing | Staphylococcus might be a protective factor for hypertension while either Acinetobacter and Sphingomonas might be are risk factor for hypertension | [53] |
| Lawrence et al., 2022 | 405 (CVD227, HI 178) | Whole Blood | Case Cohort Study | Norway | 16S rRNA gene sequencing (V3-V5) | Higher abundance of Staphylococcus, Kocuria, Enhydrobacter and low levels of Paracoccus were associated with CVDs. While Streptococcus, Paracoccus, Veillonella, and Bacteroides were in abundance in HI. | [54] |
| Khan et al., 2022a | 58 (MI 29 and 29 HI) | Whole Blood | Comparative Case control study | China | 16S rRNA genes (V3-V4) Miseq Illumina sequencing | Decreased alpha diversity in MI patients. Abundance of Bifidobacterium and Bacteroides was increased in MI patients and HI respectively. | [55] |
| Khan et al., 2022b | 210 (ACS, CCR and HI 70 each) | Whole Blood | Comparative Case control study | China | 16S rRNA genes (V3-V4) Illumina sequencing | Proteobacteria and Desulfabacterota abundance was higher in ACS and Actinobacteria in HI | [56] |
| Miscellaneous diseases and Healthy | |||||||
| Lelouvier et al., 2016 | 108 (NAFLD 22 with 86 without fibrosis) | Buffy Coat | cross-sectional study | France | 16S rDNA PCR and (V-3V4) Miseq | Increased 16S rDNA and proportions of Proteobacteria (specifically Sphingomonas, Variovorax, Bosea taxa) in NAFLD | [28] |
| Gosiewski et al., 2017 | 85 (62 sepsis 23 HI) | Whole Blood | Comparative Cohort Study | Poland | 16S rRNA gene targeted metagenomic Miseq Illumina (V3-V4) and Cultures | Healthy samples presented higher diversity than sepsis patients. Proteobacteria were lower in healthy individuals, while Actinobacteria decreased in sepsis patients. HI had predominance of anaerobic bacteria of order Bifidobacteriales | [57] |
| Li et al., 2018 | 62 (50 PP and 12 HI) | Whole blood and Neutrophils | Cohort Study | China | 16S rDNA, qPCR and targeted metagenomic sequencing V3 region (Ion Torrent PGM) | 16S rDNA gene copies were higher in patients. Bacteroidetes were high and Actinobacteria lower in patients. | [58] |
| OdleLoohuis et al., 2018 | 192 (48 SCZ, ALS 47, BPD 48, 49 HI) | Whole Blood | Cohort Study | USA | High Quality unmapped RNA sequencing | Proteobacteria, Firmicutes and Cyanobacteria were most prevalent phyla while Schizophrenia patients have diverse microbes. Bacteria and CD8+ memory T cells are inversely related. | [59] |
| Shah et al., 2019 | 40(20CKD and 20 HI) | Buffy Coat | Cross sectional Pilot Study | France | 16S rRNA (V3–V4) regions gene sequencing | Enterobacteriaceae and Pseudomonadaceae significantly higher in CKD than HC (10% versus 7%; and 23% versus 18%, respectively. | [60] |
| Schierwagen et al., 2019 | 7 LC | Venous Blood | Cohort Study | Germany | 16s rRNA Gene sequencing, Anaerobic Cultivation | Positive cultivation of Staphylococcus and Acinetobacter, Inflammatory cytokine positively correlated with abundance of blood microbiome | [23] |
| Kajihara et al., 2019 | 80 (66 LC and 14 HI) | Peripheral Blood | Cohort Study | Japan | 16s rRNA Gene sequencing, (V3-V4) | Enterobacteriaceae was higher in LC. On the contrary, the abundance of Akkermansia, Rikenellaceae and Erysipelotrichales were lower in LC | [61] |
| Whittle et al., 2019 | 10 (5 Asthma and 5 H women) | Plasma fractions | Cohort Study | United Kingdom | Cultures an16S rRNA gene sequencing | Most abundant phyla were Proteobacteria, Actinobacteria, Firmicutes and Bacteroidetes. Achromobacter and Pseudomonas were decreased in Asthma patients | [32] |
| Hammad et al., 2019 | 32 (20RA, 4AS, 4 PA, 4HI) | Serum | Cohort Study | United Kingdom | 16S rDNA sequencing V4 region | Blood dysbiosis in RA characterized by an increase in genera Halomonas, Anaerococcus, Shewanella, and members of Lachnospiraceae, while decrease in Corynebacterium 1 and Streptococcus | [62] |
| Mo et al., 2020 | 43 (28 RA and 15 HI) | Mononuclear cells | Cohort Study | China | 16S rDNA sequencing | Bacteroidetes had less abundance in RA while Candidatus Saccharibacteria was increased. | [63] |
Healthy Individuals (HI), Diabetic Patients (DP), Non Diabetic Patients (NDP), Type 2 Diabetes (T2D), Baseline obesity (BO), Cardiovascular diseases (CVDs), Myocardial Infarction (MI), High risk Cardiovascular diseases (HRCVD), Coronary Syndrome (CS), Chronic Kidney Disease (CKD), Liver cirrhosis (LC), Coronary Heart disease (CHD), Rheumatoid arthritis (RA), Pancreatitis’ patients (PP),Schizophrenia (SCZ), Amyotrophic lateral sclerosis (ALS), Bipolar disorder (BPD), Ankylosing spondylitis (AS), Psoriatic arthritis (PA), Fluorescent insitu hybridization(FISH).