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Multi-Method Characterization of the Human Circulating Microbiome

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The term microbiome describes the genetic material encoding the various microbial populations that inhabit our body. Whilst colonization of various body niches (e.g., the gut) by dynamic communities of microorganisms is now universally accepted, the existence of microbial populations in other “classically sterile” locations, including the blood, is a relatively new concept. The presence of bacteria-specific DNA in the blood has been reported in the literature for some time, yet the true origin of this is still the subject of much deliberation. The aim of this study was to investigate the phenomenon of a “blood microbiome” by providing a comprehensive description of bacterially derived nucleic acids using a range of complementary molecular and classical microbiological techniques. For this purpose we utilized a set of plasma samples from healthy subjects (n = 5) and asthmatic subjects (n = 5). DNA-level analyses involved the amplification and sequencing of the 16S rRNA gene. RNA-level analyses were based upon the de novo assembly of unmapped mRNA reads and subsequent taxonomic identification. Molecular studies were complemented by viability data from classical aerobic and anaerobic microbial culture experiments. At the phylum level, the blood microbiome was predominated by Proteobacteria, Actinobacteria, Firmicutes, and Bacteroidetes. The key phyla detected were consistent irrespective of molecular method (DNA vs. RNA), and consistent with the results of other published studies. In silico comparison of our data with that of the Human Microbiome Project revealed that members of the blood microbiome were most likely to have originated from the oral or skin communities. To our surprise, aerobic and anaerobic cultures were positive in eight of out the ten donor samples investigated, and we reflect upon their source. Our data provide further evidence of a core blood microbiome, and provide insight into the potential source of the bacterial DNA/RNA detected in the blood. Further, data reveal the importance of robust experimental procedures, and identify areas for future consideration.
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ORIGINAL RESEARCH
published: 17 January 2019
doi: 10.3389/fmicb.2018.03266
Edited by:
George Tsiamis,
University of Patras, Greece
Reviewed by:
Angel Angelov,
Technische Universität München,
Germany
Nikolaos Remmas,
Democritus University of Thrace,
Greece
*Correspondence:
Daniel Paul Tonge
d.p.tonge@keele.ac.uk
Specialty section:
This article was submitted to
Systems Microbiology,
a section of the journal
Frontiers in Microbiology
Received: 18 July 2018
Accepted: 17 December 2018
Published: 17 January 2019
Citation:
Whittle E, Leonard MO,
Harrison R, Gant TW and Tonge DP
(2019) Multi-Method Characterization
of the Human Circulating Microbiome.
Front. Microbiol. 9:3266.
doi: 10.3389/fmicb.2018.03266
Multi-Method Characterization of the
Human Circulating Microbiome
Emma Whittle1, Martin O. Leonard2, Rebecca Harrison1, Timothy W. Gant2and
Daniel Paul Tonge1*
1School of Life Sciences, Faculty of Natural Sciences, Keele University, Keele, United Kingdom, 2Centre for Radiation,
Chemical and Environmental Hazards, Public Health England, Chilton, United Kingdom
The term microbiome describes the genetic material encoding the various microbial
populations that inhabit our body. Whilst colonization of various body niches (e.g.,
the gut) by dynamic communities of microorganisms is now universally accepted, the
existence of microbial populations in other “classically sterile” locations, including the
blood, is a relatively new concept. The presence of bacteria-specific DNA in the blood
has been reported in the literature for some time, yet the true origin of this is still the
subject of much deliberation. The aim of this study was to investigate the phenomenon
of a “blood microbiome” by providing a comprehensive description of bacterially derived
nucleic acids using a range of complementary molecular and classical microbiological
techniques. For this purpose we utilized a set of plasma samples from healthy subjects
(n= 5) and asthmatic subjects (n= 5). DNA-level analyses involved the amplification
and sequencing of the 16S rRNA gene. RNA-level analyses were based upon the
de novo assembly of unmapped mRNA reads and subsequent taxonomic identification.
Molecular studies were complemented by viability data from classical aerobic and
anaerobic microbial culture experiments. At the phylum level, the blood microbiome
was predominated by Proteobacteria,Actinobacteria,Firmicutes, and Bacteroidetes.
The key phyla detected were consistent irrespective of molecular method (DNA vs.
RNA), and consistent with the results of other published studies. In silico comparison
of our data with that of the Human Microbiome Project revealed that members of the
blood microbiome were most likely to have originated from the oral or skin communities.
To our surprise, aerobic and anaerobic cultures were positive in eight of out the ten
donor samples investigated, and we reflect upon their source. Our data provide further
evidence of a core blood microbiome, and provide insight into the potential source of
the bacterial DNA/RNA detected in the blood. Further, data reveal the importance of
robust experimental procedures, and identify areas for future consideration.
Keywords: blood microbiome, unmapped reads, human, next gen sequencing (NGS), biomarker (development)
BACKGROUND
The term “microbiome” describes the genetic material encoding the various microbial populations
that inhabit our body. In contrast, the term “microbiota” refers to the viable organisms that
comprise these communities. The microbiome undertakes essential biological processes and thus
it is unsurprising that a number of disease states are associated with changes in microbiome
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composition, termed “dysbiosis.” Whilst the colonization of
specific body sites in contact with the external environment (such
as the gastrointestinal tract, skin, and vagina) by microorganisms
is both well-described and universally accepted (Markova, 2017),
the existence of microbial populations in other “classically sterile”
locations, including the blood, is a relatively new concept.
The presence of bacteria-specific DNA in the blood has been
reported in the literature for some time, yet the true origin of
this is still the subject of much deliberation. Mounting evidence
supports the existence of a blood microbiome (specifically, the
presence of bacterial genetic material) in humans (Nikkari et al.,
2001;Amar et al., 2013;Rajendhran et al., 2013;Dinakaran et al.,
2014;Kell and Pretorius, 2015;Potgieter et al., 2015;Mangul
et al., 2016;Païssé et al., 2016;Bhattacharyya et al., 2017;Li
et al., 2018) and various other species, including rodents, cats,
chickens, and cows (Sze et al., 2014;Mandal et al., 2016;Jeon
et al., 2017;Vientós-Plotts et al., 2017). This has primarily been
determined by amplification and sequencing of the bacterial 16S
rRNA gene, or via whole genome sequencing. Such studies report
the existence of bacteria-derived genetic material (DNA) within
the circulation, but do not provide evidence for the presence of
viable organisms.
Convention tells us that the blood is sterile in health, and
bacteraemia, even at 1–10 bacterial cells per milliliter whole
blood, is potentially life threatening. Despite this, several studies
have presented evidence of bacteria or bacteria-like structures
within the circulation in the absence of overt disease. It should
be noted, however, that Martel et al. (2017) report that the
bacteria-like particles often described following a range of
imaging techniques represent non-living membrane vesicles and
protein aggregates derived from the blood itself. McLaughlin
et al. (2002) surveyed the blood of 25 healthy donors and
observed the presence of pleomorphic bacteria using dark-field
microscopy, electron microscopy, polymerase chain reaction and
fluorescent in situ hybridisation, in all samples analyzed. Further,
Potgieter et al. (2015) described the presence of blood-cell
associated bacteria in a range of blood preparations using electron
microscopic techniques. Significantly, Damgaard et al. (2015)
found viable (culturable) bacteria in 62% of blood donations from
donors with no overt disease. This finding is plausible given
that various daily activities including chewing, tooth brushing,
and flossing result in the translocation of oral bacteria into
the bloodstream (Forner et al., 2006;Lockhart et al., 2008;
Parahitiyawa et al., 2009;Horliana et al., 2014), however, one
would expect such organisms to be rapidly targeted and removed
with by the immune system in healthy individuals. Kell and
Pretorius (2015) provide a detailed hypothesis for the existence
of the blood microbiome (Potgieter et al., 2015) and suggest
that it is likely composed of organisms (or parts thereof) that
translocate to the circulation from their usual place of habitation
(classical niches such as the gastrointestinal tract, oral cavity, skin,
vagina) – a process termed atopobiosis. They further describe
how this could occur via well-described physiological processes
including dendritic cells processes, via micro-fold cells, and in
disease, via dysfunctional epithelial junctions. This explanation
is supported by studies demonstrating a correlation between gut
microbiota dysbiosis and altered microbial signatures detected in
the blood (Ono et al., 2005;Sato et al., 2014;Lelouvier et al., 2016),
suggesting that the observed disease-associated blood microbiota
is a consequence of increased bacterial translocation across
the gut barrier. Furthermore, characterization of the microbial
populations in the coronary artery tissues by Lehtiniemi et al.
(2005) identified known members of the oral microbiota,
suggesting that bacteria had translocated from the oral cavities
into the bloodstream, potentially as a result of damage
caused by tooth brushing or by leakage across the mucosal
surfaces.
Various disease states are associated with blood microbiome
dysbiosis (Amar et al., 2013;Sato et al., 2014;Lelouvier
et al., 2016;Mangul et al., 2016;Ling et al., 2017), and these
changes are likely reflective of dysbiosis at a distant site(s)
with well-characterized microbial communities, and the result
of subsequent translocation. Limited evidence also suggests that
these changes may be disease-specific; Alzheimer’s disease for
example, has been associated with the detection of mostly coccus
microbes, whilst Parkinson’s disease has been associated with
both coccus and bacillus bacteria (Potgieter et al., 2015). Such
changes are of significant scientific and medical interest as
they offer opportunities for biomarker and therapeutic target
development (Lelouvier et al., 2016;Ling et al., 2017).
Due to the long-held belief that the bloodstream of healthy
individuals is sterile and since the blood is an unfavorable
compartment for the microbes due to its bacteriostatic and
bactericidal components (Mandal et al., 2016;Markova, 2017),
it is of principal significance to understand whether and how
bacteria may persist in it. Accidental contamination during the
collection of blood and or during downstream experimental
procedures has been proposed as an alternative explanation
for the existence of the blood microbiome per se. We support
this explanation for the detection of viable bacteria within
the bloodstream of healthy individuals, however, suggest that
this phenomenon does not adequately explain the existence
of the blood microbiome (the presence of bacteria-derived
nucleic acids) when one considers the number of studies
that demonstrate significant and apparently disease-specific
differences in the composition of the blood microbiome.
Moreover, examination of the bacterial taxa reported in
these studies reveal similar blood microbiota compositions
across the different studies, whereby Proteobacteria dominate
(relative abundance values typically ranging from 85 to
90%), and Firmicutes,Actinobacteria, and Bacteroidetes present
to a lesser extent (Amar et al., 2013;Lelouvier et al.,
2016;Païssé et al., 2016;Olde Loohuis et al., 2018). This
suggests the existence of a core blood microbiome profile
that persists independent of study environment or analytical
methodology.
Using a range of complementary molecular and classical
molecular biology techniques, the human circulating microbiome
was characterized in unparalleled detail; at the DNA level, the
16S rRNA gene was amplified and sequenced, at the RNA level,
almost 500,000,000 unmapped mRNA reads were assembled
and mapped to known taxa, and finally, viability data was
generated using classical aerobic and anaerobic microbial culture
experiments. The experimental approach is detailed in Figure 1.
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FIGURE 1 | Schematic representation of the multiple-method circulating microbiome characterization approach implemented herein. NB: Biomarker and
mechanistic data are not included within the scope of this publication and appear elsewhere.
MATERIALS AND METHODS
Donor Samples
Atopic asthmatic individuals (n= 5) with physician-diagnosed
house dust mite allergy, and gender and age-matched healthy
control subjects (n= 5) were recruited to the study via SeraLabs
Limited in accordance with the following criteria (Table 1).
Whole blood was drawn, following alcohol cleansing of the skin
surface, into EDTA containing tubes and stored on ice prior to
centrifugation at 1000 ×gto obtain the plasma component. All
samples were analyzed anonymously, and the authors obtained
ethical approval (Keele University ERP3) and written informed
consent to utilize the samples for the research reported herein.
DNA-Level: Meta-Taxonomic
Characterization
The circulating microbiome was investigated at the DNA level
by amplification and sequencing of the bacterial 16S ribosomal
gene using oligonucleotide primers that target variable region
4 (Kozich et al., 2013) (Table 2). Direct amplification of the
V4 region was performed using the Phusion Blood Direct kit
(Thermo Fisher Scientific) alongside a negative control reaction
(in which blood was replaced with molecular biology grade
water) that underwent the complete experimental procedure.
Amplification was performed in triplicate as 20 µl reactions
containing; 1.0 µl plasma, 10 µl 2X Phusion blood PCR buffer,
0.4 µl Phusion Blood II DNA polymerase, 1.0 µl of each forward
TABLE 1 | Donor population characteristics.
Patient Criteria
Have a BMI <30
Be non-smokers
Were diagnosed with atopic asthma during childhood
Have severe/ poorly controlled symptoms
Are not on current oral steroid treatment
Must be allergic to house dust mite
Must not have diabetes, COPD, or hypertension
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and reverse oligonucleotide primer (10 µM), and 6.6 µl of UV-
treated molecular biology grade water. Cycling parameters were
as follows; an initial 5 min denaturation step at 98C followed by
33 cycles of; denaturation (1 s at 98C), annealing (5 s at 55C),
and extension (15 s at 72C), and a final extension at 72C for
7 min.
Amplicons resulting from triplicate reactions were combined
and purified using the MinElute PCR purification kit (Qiagen)
prior to a further 7 cycles of PCR using AccuPrime Pfx
SuperMix and a pair of V4 oligonucleotide primers we developed
to incorporate the Illumina XT adapter in preparation for
sequencing (Table 2). Cycling parameters were as follows;
initial denaturation for 2 min at 95C followed by 7 cycles
of; denaturation (15 s at 95C), annealing (30 s at 55C), and
extension (25 s at 68C), and a final extension at 68C for 10 min.
PCR products were purified using the AMPure XP magnetic
beads (Agencourt) at a ratio of 0.8 beads to sample (v/v), eluted
in 20 µl molecular biology grade water, and quantified using the
Qubit 3.0 high-sensitivity DNA kit. Amplicons were barcoded
using the Nextera DNA library kit, multiplexed, and sequenced
using the Ilumina MiSeq system with a 250 bp paired-end
read metric. Bioinformatic analysis was performed using QIIME
(Caporaso et al., 2010) implemented as part of the Nephele
16S paired-end QIIME pipeline using closed reference clustering
against the SILVA database (Quast et al., 2013) at a sequence
identity of 99%. All other parameters remained as default.
RNA-Level: De novo Assembly of
Unmapped RNA Reads
For the purposes of increasing our understanding of the
molecular processes that are deregulated in patients with
atopic asthma, we previously performed whole transcriptome
sequencing on RNA extracted from each donor plasma sample
(data currently unpublished). Here, we hypothesized that the
non-mapping (likely non-human) reads that often result from
such analyses would represent microbial community members
that were present in the blood at the time of RNA extraction.
To this end, RNA reads were mapped to the Homo sapiens
genome version hg38 using Tophat with default parameters
(Trapnell et al., 2012). Reads failing to map to hg38 were
identified from the resulting BAM file and reads, in fastq format,
extracted using bedtools bamtofastq. In order to streamline
our strategy, a single de novo transcriptome was produced
by concatenating all of the unmapped reads produced from
the entire study, and assembling these using Trinity (Haas
et al., 2013) to form features representative of candidate non-
human genes. To increase computational efficiency, the total
read population was subsampled to a depth of 1, 10, 25, and
100 M, and the number of reads that these features explained
computed by building a bowtie2 index out of each resulting
transcriptome, and mapping the unmapped read population
from each sample back to it. The transcriptome assembly with
the highest mapping rate was used for further analysis as
follows: (1) Abundance estimation – the transcriptome was
indexed for bowtie2 and the number of reads mapping to
each feature determined for each of our donor samples using
RSEM (Li and Dewey, 2011). (2) A matrix of expression values
was produced using the abundance_estimates_to_matrix.pl
script packaged with Trinity (Grabherr et al., 2011). (3)
Statistical analysis – a differential expression analysis was
conducted to identify candidate non-human genes that were
significantly differentially expressed between the disease and
disease-free donors using edgeR (Robinson et al., 2010). (4)
Identification – the taxonomic identity of each assembled
feature was determined using Kraken (Wood and Salzberg,
2014) and visualized using Pavian (Breitwieser and Salzberg,
2016).
Classical Culture: Bacterial Viability
Classical microbiological culture, using a range of substrates,
was carried out to determine whether the human plasma
samples contained any viable bacterial cells, i.e., those capable
of proliferation. For each sample, 250 µl plasma was inoculated
into 9 ml of brain heart infusion broth and incubated for 5 days
at 37C. For each culture a negative control was generated,
whereby 9 ml of brain heart infusion broth was inoculated with
250 µl of ultra-violet sterilized distilled water and incubated
for 5 days at 37C. The inoculated broth was plated onto
agar plates (Columbia agar +5% horse blood; CLED medium;
A.R.I.A +horse blood) and incubated under either aerobic
(Columbia blood agar; CLED medium) or anaerobic (A.R.I.A
agar) conditions at 37C for a minimum of three days. Bacterial
growth was evaluated by sight, and a selection of individual
colonies from each plate was selected for identification by total
16S gene amplification and Sanger sequencing.
RESULTS AND DISCUSSION
Donor Characteristics
This study utilized samples originally sourced for the molecular
characterization of asthma pathogenesis1. The donor population
were all female (due to the characteristics of the clinical donor
population at the time of collection), and all “never smokers.”
The asthmatic population were 39.6 years in age (range 19–52)
with a mean body mass index of 24.4 (range 21.5–27.8) and
all had physician-diagnosed atopic asthma resulting from house
dust mite allergy. The control population were 39.4 years in age
(range 23–49) with a mean body mass index of 24.3 (range 21.0–
26.4) and were disease-free. There were no statistically significant
differences in age (P= 0.98) or BMI (P= 0.93) between the two
groups (Table 3).
DNA-Level Circulating Microbiome –
Community Structure
The presence of bacterial DNA within the blood of our study
cohort was evaluated by amplification and sequencing of the
16S RNA gene variable region 4. A negative experimental
control sample mirrored our study samples through the entire
experimental procedure downstream of venepuncture. This
involved using ultra-violet treated molecular biology-grade water
in replacement of human blood during PCR amplification of
1https://doi.org/10.1101/446427
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TABLE 2 | Oligonucleotide primer sequences.
Primer Name Sequence (50–30) Length
V4_F GTGCCAGCMGCCGCGGTAA 19
V4_R GGACTACHVGGGTWTCTAAT 20
V4_XT_F TCGTCGGCAGCGTCAGATGTGTATAAGAGACAGGTGCCAGCMGCCGCGGTAA 52
V4_XT_R GTCTCGTGGGCTCGGAGATGTGTATAAGAGACAGGGACTACHVGGGTWTCTAAT 54
TABLE 3 | Donor population characteristics.
Donor Age (years) BMI (kg/m2) Smoking History Diagnosis
BRH1017873 50–60 27.8 Never Atopic Asthma, HDM
BRH1017874 30–40 27.3 Never Atopic Asthma, HDM
BRH1017875 40–50 23.3 Never Atopic Asthma, HDM
BRH1017876 10–20 21.5 Never Atopic Asthma, HDM
BRH1017877 40–50 22.3 Never Atopic Asthma, HDM
BRH1017878 40–50 26.4 Never Healthy
BRH1017879 20–30 21 Never Healthy
BRH1017880 40–50 26.4 Never Healthy
BRH1017881 40–50 24.9 Never Healthy
BRH1017882 30–40 22.7 Never Healthy
the 16S rRNA V4 region. The negative control PCR product
was then submitted to all downstream applications that the
human blood underwent. This included bead-based purification
of the 16S rRNA V4 amplicons, agarose gel electrophoresis, XT-
tagging, library preparation and sequencing of the 16S rRNA V4
amplicons.
Using QIIME (Caporaso et al., 2010) implemented as part
of Nephele, a total of 243, 853 sequencing reads from the
amplified V4 region passed quality assessment (mean = 24,385
reads per sample; range = 10,742–35,701 reads). The results of
our taxonomic classification are shown in (Figures 2A–D) at the
phylum and genus levels.
Our negative control reaction generated a small number
of reads that were identified as the following genera;
Halomonas (6 reads),Corynebacterium (64),Staphylococcus
(24),Ralstonia (1726), Stenotrophomonas (460),Pseudomonas
(276),Escherichia-Shigella (2420), and Ruminococcus (405),
but was overwhelmingly composed of reads mapping to the
genus Serratia (18000). These genera have been reported
previously as contaminants of next generation sequencing
experiments (Laurence et al., 2014;Salter et al., 2014)
but importantly here, were either distinct from the taxa
identified within our samples, or present at much lower
levels.
At the phylum level, the blood microbiome was predominated
by Proteobacteria (88% of all bacterial DNA in the control
population, and 80.9% in the asthmatic population) followed by
Actinobacteria (control = 7.8%, asthmatic = 7.1%), Firmicutes
(control = 3.5%, asthmatic = 9.2%) and Bacteroidetes
(control = 0.1%, asthmatic = 2.2%). These findings mirror
previous studies (Amar et al., 2013;Lelouvier et al., 2016;Païssé
et al., 2016;Olde Loohuis et al., 2018) and further support the
notion of a core blood microbiome predominated by four key
phyla.
At the genus level, our blood samples were predominated by
the genus Achromobacter (Gyarmati et al., 2016) which accounted
for 51.1 and 45.3% of the total bacterial DNA detected in the
control and asthma donors, respectively. To a lesser extent, the
blood samples also comprised members of the Pseudomonas
(12.8%, 7.5%) (Dinakaran et al., 2014;Damgaard et al., 2015;
Païssé et al., 2016), Serratia(0.9%, 11.6%) (Moriyama et al.,
2008), Sphingomonas (3.8%, 5.1%) (Lelouvier et al., 2016;Païssé
et al., 2016), Staphylococcus (5.5%, 2.8%) (Such et al., 2002;
Marques da Silva et al., 2003;Damgaard et al., 2015;Païssé
et al., 2016), Corynebacterium (3.2%, 5.5%) (Dinakaran et al.,
2014;Païssé et al., 2016), and Acinetobacter (3.7%, 2.8%) (Païssé
et al., 2016) genera. The genus Serratia was excluded from further
analysis as the study samples presented with less reads than
did the corresponding negative control reaction and thus it was
considered a contaminant.
Whilst all genera found have been previously described in
the blood (see references), the predominance of Achromobacter,
which is not classically associated with the blood microbiome,
warrants further consideration. Indeed, Achromobacter
has been detected abundantly in the lower respiratory
tract of healthy mice (Singh et al., 2017), humans (HPM
airway dataset), and in various respiratory conditions
(Segal et al., 2014;Hogan et al., 2016). Furthermore, no
Achromobacter was detected in our experimental control
reactions suggesting that its presence is not the result of
experimental contamination.
Although differential composition of the blood microbiome
in response to pathology was not the main focus of this study,
we performed principal coordinates analysis and despite the
relatively small sample set, this revealed good separation between
the two treatment groups based upon their microbiome profile,
suggesting that the blood microbiome community was altered in
the asthmatic subjects (Figure 3).
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FIGURE 2 | Relative abundance of the most abundant taxa (>1%) as determined by amplification and sequencing of the 16S rRNA gene variable region 4. Data are
mean abundance expressed as a percentage of the total bacterial sequence count. (A) Phylum-level data grouped by condition, (B) Genus-level data grouped by
condition, (C) Phylum-level individual sample data, and (D) Genus-level individual sample data.
FIGURE 3 | Principal coordinates analysis of weighted unifrac distances for
control (blue) and asthmatic (red) blood microbiome profiles. Each dot
represents an individual sample, and the microbiome of samples that appear
more closely together are more similar.
DNA-Level Circulating Microbiome –
Likely Origins
In accordance with our hypothesis that the blood microbiome
exists as a consequence of bacterial translocation from other
microbiome niches within the body, we compared the data
generated herein with gastrointestinal tract, oral cavity, and
skin data made available by the Human Microbiome Project
(HMP). In each case, the HMP data and our own were
combined, weighted UniFrac distances calculated, and a principal
coordinates analysis performed. Figure 4 demonstrates that the
blood microbiome of our control and asthmatic donors clustered
more closely in PCoA space with the oral cavity and skin HMP
data, than it did with the gastrointestinal tract HMP data. This
suggests that the blood microbiome community is perhaps more
likely to result from the translocation of organisms from the
oral cavity and skin, than from organisms that colonize the
gastrointestinal tract.
Various daily activities including chewing, tooth brushing
and flossing have been shown to result in the translocation
of bacteria from the oral cavity into the bloodstream (Forner
et al., 2006;Lockhart et al., 2008;Parahitiyawa et al., 2009;
Horliana et al., 2014). Further, the skin has a distinct microbial
community and is susceptible to injury, and thus represents a
large surface area through which such organisms may translocate
to the bloodstream. It is important here to consider sources
of contamination; venepuncture, the process through which the
majority of blood samples are obtained, is recognized as a cause
of transient bacteraemia (Depcik-Smith et al., 2001), and despite
the use of preventative measures such as alcohol cleansing of the
skin prior to breaking the surface, there remains the possibility
that organisms entered the sample from the skin via this route.
One important, but often overlooked limitation of DNA-based
microbiome characterization is that DNA persists post-mortem,
even in the presence of harsh environmental conditions. From
such analyses it is therefore impossible to confirm whether an
organism is present and viable, is present but non-viable, or
whether the organism has since left the environment in question
yet it’s DNA persists.
RNA-Level Circulating Microbiome –
Community Structure
We hypothesize that some of the non-mapping (likely non-
human) reads that often result from whole transcriptome
analyses (RNA-seq) represent microbial community members
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FIGURE 4 | Principal coordinates analysis of weighted unifrac distances between variable region 4 16S sequencing data from our donors and the Human
Microbiome Project Gut, Oral Cavity, and Skin data. Each dot represents an individual sample, and the microbiome of samples that appear more closely together are
more similar. In each case, our control donor samples appear in blue, and our asthmatic donor samples appear in red. Further sample details are provided beneath
each figure, and the number of datasets representing each anatomic location is provided in brackets.
that were present (or parts thereof) in the blood at the time
of RNA extraction. Furthermore, given the unstable nature of
extracellular circulatory RNA (Tsui et al., 2002) in addition to
the presence of circulatory ribonucleases that actively degrade
RNA (Segal et al., 2014), we suggest that the detection of
bacterial RNA goes further toward confirming the recent
presence of these microbes within the blood when compared
with DNA-based approaches. From our previous studies of the
circulating transcriptome of our donor community, a total of
439,448,931 paired RNA reads failed to map to the human
genome. These reads were used for the following analyses
as randomly subsampled populations of 1, 10, 25, and 100
million read pairs. Mapping the total read population back
to the subsampled populations allowed us to assess how
well each subsampled population approximated the starting
(entire, 440 M read) population. Data revealed only
marginal improvements in whole community representation as
the subsampled population increased (1, 10, 25, and 100 M
represented 65.05, 66.05, 66.81, and 64.24% of the total read
population). A subsampled population of 25 million reads (25 M)
provided an acceptable balance between read representation
and computational efficiency and was therefore used for
transcriptome assembly. The transcriptome comprised 2050
candidate “non-human genes” with a mean GC content of
53%. Ten-percent of these genes were greater than 517 bp,
and over half were at least 263 bp. Taxonomic identification of
each assembled feature was determined using Kraken (Wood
and Salzberg, 2014) and this revealed that 729 of the 2050
features were of bacterial origin and seven features were from
archaea [pertaining to the taxa Thermoplasmata, which has
been previously associated with the human microbiome (Lurie-
Weinberger and Gophna, 2015)] (Figure 5). Although we
identified 13 features of apparent viral origin, we did not consider
these in any further detail given they appeared to pertain to the
Moloney murine leukemia virus, a commonly utilized reverse
transcriptase used in molecular procedures. It should be noted
that the Kraken database does not include fungi, and therefore
this kingdom was not represented within our data.
At the phylum level, the whole transcriptome data was
predominated by assembled Proteobacteria sequences (379
sequences, 52%), followed by Firmicutes (143, 19.8%),
Actinobacteria (112, 15.5%) and Bacteroidetes (35, 4.8%). In
considering the total number of reads mapping to each feature,
379.4 M reads mapped to bacterial features (out of a total of
395 M reads). Of those reads mapping to bacterial-derived
sequences, Proteobacteria (74.9%, 47.0%; Control, Asthma) and
Firmicutes (19.5%, 48.0%) predominated with, Actinobacteria
(0.01%, 0.04%) and Bacteroidetes (0.05%, 0.008%) present to
a much lesser extent. These findings support our DNA-level
phylum data and mirror previous studies (Amar et al., 2013;
Lelouvier et al., 2016;Païssé et al., 2016;Olde Loohuis et al.,
2018).
At the genus level, the whole transcriptome data was
predominated by the genera Paenibacillus (17.8%, 44.6%;
Control, Asthma reads) (Sáez-Nieto et al., 2017), Escherichia
(11.8%, 13.1%) (Such et al., 2002;Francés et al., 2004;
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FIGURE 5 | Taxonomic classification of each feature assembled from unmapped RNA sequencing reads using Trinity and identified using Kraken. The numbers
present by each taxonomic classification refer to the number of features classified as such (e.g., 379 assembled features were identified as Proteobacteria). D –
domain, P – phylum, F – family, G – genus, S – species.
FIGURE 6 | Taxonomic classification of total 16S data generated by colony PCR and Sanger sequencing. The numbers present by each taxonomic classification
indicate the number of colonies that were identified with that identity. D – domain, P – phylum, F – family, G – genus, S – species.
Dinakaran et al., 2014;Païssé et al., 2016), Acinetobacter (0.7%,
0.4%) (Païssé et al., 2016), Pseudomonas (0.8%, 0.1%) (Bhatt
et al., 2014;Dinakaran et al., 2014;Damgaard et al., 2015;Païssé
et al., 2016) and Propionibacterium (0.5%, 0.2%) (Marques da
Silva et al., 2003;Bhatt et al., 2014;Dinakaran et al., 2014;
Damgaard et al., 2015). With the exception of Paenibacillus,
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TABLE 4 | Identification of cultured organisms using 16S colony PCR and Sanger sequencing.
Growth
Condition
Control Samples Asthma Samples
BRH1017878 BRH1017879 BRH1017880 BRH1017881 BRH1017882 BRH1017874 BRH1017875 BRH1017876 BRH1017877
Aerobic
Growth
Kocuria
rhizophila
Micrococcus
luteus
Staphylococcus
haemolyticus
Staphylococcus
epidermidis
Propionibacterium
acnes
Staphylococcus
haemolyticus
Culture Neg Staphylococcus
haemolyticus
Culture Neg Corynebacterium
halotolerans
Staphylococcus
epidermidis
Anaerobic
Growth
Culture Neg Culture Neg Staphylococcus
epidermidis
Staphylococcus hominis Culture Neg Culture Neg Culture Neg Culture Neg Staphylococcus
epidermidis
Culture Neg denotes no bacterial growth on the substrates used.
all genera detected via de novo transcriptome assembly were
also present in our DNA-level data and all genera found have
been previously described in the blood (see references). The fact
that Paenibacillus was present within our RNA-level analyses yet
absent from our DNA-level data led us to consider whether it
could have been introduced as a contaminant during the RNA
extraction, library preparation or sequencing procedures. Given
that negative control reactions are not routinely conducted for
RNA-seq type applications, we were unable to experimentally
confirm this. However, we did identify from the literature that
this genus has been reported as a common reagent and laboratory
contaminant, albeit at the DNA level (Salter et al., 2014).
Nevertheless there appeared to be little consistency in its presence
within our sample set (mean % of reads 39.5 ±40.3%) and
we noted a difference in abundance between our experimental
groups despite all preparation procedures being the same. The
exact source of this RNA thus remains open to speculation.
Classical Culture – Presence of Viable
Organisms
The presence of viable, proliferating bacteria in the blood was
assessed using growth culture assays as previously described.
Bacterial cultures were positive for 80% of blood samples assayed
(8 out of 10 samples; 4 control blood samples and 4 asthma
blood samples), whilst all negative control plates had no growth
as expected. Negative cultures were repeated on two further
occasions to confirm this status. These results are relatively
consistent with previous studies, whereby 2–100% of blood
samples were positive for bacterial growth (Wilson et al., 1975;
Domingue and Schlegel, 1977;Jiménez et al., 2005;Damgaard
et al., 2015;Panaiotov, 2018). Unexpectedly, bacterial growth
was observed in aerobic conditions for all culture-positive blood
samples, but anaerobic growth was only observed for four of
the culture-positive blood samples. This is contradictory to
previous studies, where bacterial growth from blood-cultures
has predominately been achieved using anaerobic conditions
(Jiménez et al., 2005;Damgaard et al., 2015).
In all instances, bacterial growth was monoculture on
microscopy and thus 16S colony PCR (amplifying the entire
16S rRNA gene) and Sanger sequencing was conducted on a
three independent colonies per plate for identification purposes.
Bacteria were identified using Sanger sequencing followed by
classification with Kraken. Bacteria isolated from the aerobic
cultures included the following genera; Staphylococcus (49
sequences), Micrococcus (12), Kocuria (6), Corynebacterium
(6) and Propionibacterium (1). Bacteria isolated from the
anaerobic cultures were less variable and included members
from the facultatively anaerobic Staphylococcus genus only
(Figure 6). These genera belong to the phyla Actinobacteria
(Corynebacterium,Kocuria,Micrococcus) and Firmicutes
(Staphylococcus) and were all represented in our 16S DNA level
data (Figure 4) and detected within our RNA data. Individual
sample data is presented in Table 4. It is noteworthy that,
with the exception of Kocuria, all bacteria identified displayed
some of the highest total relative abundance scores in the 16S
sequencing results; Corynebacterium (4.2%), Kocuria (0.2%),
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Micrococcus (1.30%), and Staphylococcus at 4.3%. Due to the
long-held belief that the bloodstream of healthy individuals
is sterile and since the blood is an unfavorable compartment
for the microbes due to its bacteriostatic and bactericidal
components; here we consider the likely source of these viable
organisms. The skin microbiome is dominated by members of
the genera Corynebacterium,Micrococcus,Staphylococcus, and
Propionibacterium, the proportions of which vary markedly
between individuals (Tett et al., 2017). Furthermore, several
studies report the presence of the genus Kocuria on the skin
of humans and other mammals (Grice et al., 2008;Cosseau
et al., 2016;McIntyre et al., 2016). We therefore suggest that the
organisms detected through our microbial culture experiments
most likely originate from the skin. Whilst transient bacteraemia
due to a breach of the skin barrier is an accepted occurrence, one
would expect such organisms to be rapidly targeted and removed
by the immune system.
We therefore suggest that the viable organisms detected
through classical microbial culture analysis are the result of
venepuncture contamination whereby organisms from the skin
are drawn into the vacutainer, contaminating the sample. An
alternative hypothesis suggests that these bacteria were present
in the blood in a dormant state (i.e., not contaminants), and were
somehow revived following pre-growth in brain heart infusion
broth prior to plating [see Kell and Pretorius, 2015 for a detailed
description of this hypothesis (Potgieter et al., 2015)], however,
this hypothesis is still under intense investigation.
CONCLUSION
This study utilized a range of molecular and classical
microbiology approaches to characterize the human blood
microbiome in unparalleled detail. Our DNA and RNA-based
studies revealed a diverse community of bacteria, the main
members of which having been described in a range of other
studies and therefore providing further evidence of a core blood
microbiome. Although disease associated changes in the blood
microbiome were not the focus of this study, the fact we identified
such changes is encouraging and supports efforts to identify
circulating microbiome signatures indicative of disease.
Whilst we attribute the finding of viable organisms in our
plasma samples to venepuncture-associated contamination of
the blood sample (and make recommendations to avoid this in
future) and or the phenomena of dormancy, the presence of these
viable organisms does not undermine our exciting molecular
data that reports an abundance of bacteria-associated DNA and
RNA within the blood, likely present due to translocation from
classical microbiome niches (such as the gut, oral cavity and skin),
and with the clear potential to be developed as a biomarker of
microbiome status at distant anatomical sites.
On reflecting upon our experimental approach, we make the
following recommendations for future studies:
(1) Significant attention should be paid to blood collection
procedures as any contamination occurring at this stage
impacts upon all downstream procedures. In addition to
alcohol cleansing of the skin (as performed in this study),
we recommend that the first volume drawn is diverted
to a secondary tube, and analyzed separately. This will
allow investigation of the contribution that venepuncture-
associated contamination makes, and allow robust analysis
of the dormancy hypothesis.
(2) The inclusion of negative control reactions that are subject
to the whole range of experimental procedures, including
library preparation and sequencing, is absolutely essential.
(3) Where possible, RNA-seq studies used for unmapped read
assembly should include negative control samples that are
subject to all of the experimental procedures alongside
the study samples. This will allow an appraisal of how
significant reagent/laboratory procedure contamination
is in these studies. Often the use of RNA-seq derived
unmapped reads for microbiome characterization is a
“secondary use,” and this is simply not possible.
(4) Seminal studies are still required to satisfactorily investigate
the phenomenon of bacterial translocation from well-
characterized microbiome niches to the blood.
DATA AVAILABILITY
The sequencing data utilized in this project can be found in the
Sequence Read Archive, NIH, under the identifier SUB4654957.
ETHICS STATEMENT
This study was carried out in accordance with the
recommendations of Keele Ethical Review Panel 3 (ERP3),
Keele University with written informed consent from all subjects
obtained by SeraLab limited who supplied the blood samples used
herein. All subjects gave written informed consent in accordance
with the Declaration of Helsinki.
AUTHOR CONTRIBUTIONS
DT conceived the novel unmapped read approach to microbiome
analysis, carried out the bioinformatic method development, and
prepared the original manuscript. DT, ML, and TG designed
the original study who generated the RNA sequencing data. EW
conducted the 16S work, classical microbiology and assisted in
the interpretation of the findings. RH managed the classical
microbiology. DT, ML, EW, RH, and TG approved the final
manuscript.
ACKNOWLEDGMENTS
This study used the Nephele platform from the National Institute
of Allergy and Infectious Diseases (NIAID) Office of Cyber
Infrastructure and Computational Biology (OCICB) in Bethesda,
MD. This article was published as a pre-print with the following
https://doi.org/10.1101/359760 (Whittle et al., 2018).
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Conflict of Interest Statement: 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.
Copyright © 2019 Whittle, Leonard, Harrison, Gant and Tonge. This is an open-
access article distributed under the terms of the Creative Commons Attribution
License (CC BY). The use, distribution or reproduction in other forums is permitted,
provided the original author(s) and the copyright owner(s) are credited and that the
original publication in this journal is cited, in accordance with accepted academic
practice. No use, distribution or reproduction is permitted which does not comply
with these terms.
Frontiers in Microbiology | www.frontiersin.org 12 January 2019 | Volume 9 | Article 3266
... Moreover, several studies have suggested the existence of tissue microbiota either in humans or in mice [15][16][17][18]. The 16S rRNA gene signature was also demonstrated in the blood of healthy humans (primarily leukocyte and platelet fractions) [19] or patients [20,21] as well as in the circulation of animals [22][23][24]. These key factors illustrate the crosstalk line between the gut microbiota, circulation, and tissues [25]; that is, the gut microbiota enter into the circulation through leakage and locate into tissues and change into tissue microbiota/tumor type-specific intracellular bacteria. ...
Article
Full-text available
The tumor and tissue microbiota of human beings have recently been investigated. Gut permeability is known as a possible resource for the positive detection of tissue bacteria. Herein, we report that microbiota were detected in high abundance in the hepatocytes of healthy rats and that they were shared with the gut microbiota to an extent. We assessed male Sprague Dawley (SD) rats for the 16S ribosomal ribonucleic acid (rRNA) gene. After the rats were sacrificed by blood drainage from the portal vein, we extracted total deoxyribonucleic acid (DNA) from their ileal and colonic contents and liver tissues. The V3–V4 region of the 16S rRNA gene was amplified by polymerase chain reaction (PCR) and sequenced using an Illumina HiSeq 2500 platform. Sequences were assigned taxonomically by the SILVA database. We also detected bacterial lipopolysaccharide (LPS) and lipoteichoic acid (LTA) in situ using immunofluorescence (IF) and western blotting and the 16S rRNA gene using fluorescent in situ hybridization (FISH). In the livers of six rats, we detected 54,867.50 ± 6450.03 effective tags of the 16S rRNA gene and clustered them into 1003 kinds of operational taxonomic units (OTUs; 805.67 ± 70.14 , 729–893). Rats showed conservation of bacterial richness, abundance, and evenness. LPS and the 16S rRNA gene were detected in the nuclei of hepatocytes. The main function composition of the genomes of annotated bacteria was correlated with metabolism ( 79.92 ± 0.24 % ). Gram negativity was about 1.6 times higher than gram positivity. The liver microbiome was shared with both the small and large intestines but showed significantly higher richness and evenness than the gut microbiome, and the β-diversity results showed that the liver microbiome exhibited significantly higher similarity than the small and large intestines ( P < 0.05 ). Our results suggest that the bacteria in the liver microbiome are hidden intracellular inhabitants in healthy rat livers.
... We still need to learn more about how the skin microbiome differs between migratory and sedentary wild fish populations. Considering the importance of the microbiome as a biomarker and the need to adopt less costly and invasive procedures, the concept of "circulating microbiome DNA" (cmDNA) has been developed as an alternative to studying the microbiome in clinical settings [10]. Since the middle of the 20th century, we have known that DNA fragments are present in the blood [11], but it is only in recent years that the advent of NGS methods has allowed us to better understand the origin of these circulating DNA fragments. ...
Preprint
Our understanding of how microbiome signatures are modulated in wild fish populations remains poorly known and has, until now, mostly been inferred from studies in commercial and farmed fish populations. Here, we have studied for the first time changes in the skin and blood microbiomes of the Salmo trutta population of the volcanic Kerguelen archipelago located at the northern limit of the Antarctic Ocean. Kerguelen is a natural framework of population expansion and a likely situation under further climate change in distribution areas. Our results showed that S. trutta of Kerguelen has a microbiome signature distinct from those of salmonids of the Northern Hemisphere. Our study also revealed that the skin and blood microbiomes differ between sedentary and migratory S. trutta. While 18 phyla were shared between both groups of trout, independent of the compartment, six phyla were unique to migratory trout. Further analyses showed that microbiome signatures undergo significant site-specific variations that correlate, in some cases, to the peculiarity of specific ecosystems. Our study also revealed the presence of potential pathogens at particular sites and the impact of abiotic factors on the microbiome, most notably due to the volcanic nature of the environment. This study contributes to a better understanding of the factors that modulate the microbiome signatures of migratory and sedentary fish populations. It will also help better monitor climate change's impacts on the colonization process in the sub-Antarctic region.
... Moreover, several studies have suggested the existence of tissue microbiota either in humans or in mice [15][16][17][18]. The 16S rRNA gene signature was also demonstrated in the blood of healthy humans (primarily leukocyte and platelet fractions) [19] or patients [20,21] as well as in the circulation of animals [22][23][24]. These key factors illustrate the crosstalk line between the gut microbiota, circulation, and tissues [25]; that is, the gut microbiota enter into the circulation through leakage and locate into tissues and change into tissue microbiota/tumor type-speci c intracellular bacteria. ...
Preprint
Full-text available
The tumor and tissue microbiota of human beings have recently been investigated. Gut permeability is known as a possible resource for the positive detection of tissue bacteria. Herein, we report that microbiotawere detected in high abundance in the hepatocytes of healthy rats, and that they were shared with the gut microbiota to an extent. We assessed male Sprague Dawley (SD) rats for the 16S ribosomal ribonucleic acid (rRNA) gene. After ratswere sacrificed by blood drainage from the portal vein, we extracted total deoxyribonucleic acid (DNA) from their ileal and colonic contents and liver tissues. The V3–V4 region of the 16S rRNA gene was amplified by polymerase chain reaction (PCR) and sequenced using an Illumina HiSeq 2500 platform. Sequences were assigned taxonomically by the SILVA database. We also detected bacterial lipopolysaccharide (LPS) and lipoteichoic acid (LTA) in situ using immunofluorescence (IF) and western blotting and the 16S rRNA gene using fluorescent in situ hybridization (FISH). In the livers of six rats, we detected 54,867.50 ± 6450.03 effective tags of the 16S rRNA gene and clustered them into 1003 kinds of operational taxonomic units (OTUs; 805.67 ± 70.14, 729–893). Individuals showed conservation of bacterial richness, abundance, and evenness. LPS and the 16S rRNA gene were detected in the nuclei of hepatocytes. The main function composition of the genomes of annotated bacteria was correlated with metabolism (79.92 ± 0.24%). Gram negativity was about 1.6 times higher than gram positivity. The liver microbiome was shared with both the small and large intestines, but showed significantly higher richness and evenness than the gut microbiome, and the β-diversity results showed that the liver microbiomeexhibited significantly higher similarity than the small and large intestines ( P < 0.05). Our results suggest that the bacteria in the liver microbiome are hidden intracellular inhabitants in healthy rat livers.
... 7 Due to the long-held belief that the bloodstream of healthy individuals is sterile and since the blood is an unfavorable compartment for the microbes due to its bacteriostatic and bactericidal components. 6 Recent studies, particularly cross-sectional studies targeting the 16 S rRNA gene, have revealed a dominant group of blood-borne bacterial phyla (i.e., Proteobacteria, followed by Actinobacteria, Firmicutes, and Bacteroidetes), 8,9 and demonstrate the consistency of the human blood microbiota across time. Moreover, examination of the bacterial taxa reported in these studies reveals similar blood microbiota compositions across the different studies, whereby Proteobacteria dominate (relative abundance values typically ranging from 85% to 90%), and Firmicutes, Actinobacteria, and Bacteroidetes present to a lesser extent. ...
Article
Full-text available
Background: In almost every country, cardiovascular diseases are the major cause of death, which are responsible for 17.7 million deaths worldwide, or 54% of all deaths. However, the latest evidence has shown that non-communicable diseases such as obesity, diabetes, and cardiovascular events are significantly influenced by the blood microbiota and circulating metabolites. Methods: We searched online databases for the most recent related papers through the comprehensive international databases of the Institute of PubMed/ MEDLINE, ISI/WOS, and Scopus up to August 2022, using MESH terms and the related keywords in the English language. Considering the titles and abstracts, unrelated studies were excluded. The full texts of the remained studies were evaluated by authors, independently. Then, the studies' findings were assessed and reported. Results: The study demonstrated that the bacterial profiles of patients with cardiovascular diseases and healthy individuals are significantly different. The diseased patients showed a significantly high abundance of phylum Proteobacteria, an important Proteobacterial component known as lipopolysaccharides that has been linked to the pathogenesis of cardiovascular disease, while phylum Firmicutes were found in healthy individuals. It suggests that Proteobacteria has a direct role in the onset of cardiovascular disease. Conclusion: We focused on the blood bacterial composition and circulating microbial metabolites in their relationship with the etiology and onset of cardiovascular disease. However, the various genera and species in the results reported were not always identical. Therefore, the microbial community structure of blood was more complicated and thus required a more in-depth exploration.
... The concept of the circulating microbiome is thus particularly well adapted to the development of routine and predictive biomarkers. The utility of this approach has recently been demonstrated in clinical settings, offering a new perspective for the development of biomarkers in ecology 21-24 similar to those described for several diseases in humans 16,20,25 . In fact, the existence of a blood microbiome is a concept that is now widely accepted not only in humans but also in animals, including pigs, broiler chickens, camels, cows, goats, cats and dogs 21,23,24, 26-29 . ...
Preprint
Full-text available
The establishment of long-term microbiome-based monitoring programs is critical for the management and conservation of wild fish populations in response to climate change. In most cases, these studies have been conducted on gut and, to a lesser extent, skin (mucus) microbiomes. Here, we exploited the concept of liquid biopsy to study the circulating bacterial microbiome of two Northern halibut species of economic and ecological importance. Amplification and sequencing of the 16S rRNA gene was achieved using a single drop of blood fixed on FTA™ cards to identify the core blood microbiome of Atlantic and Greenland halibut populations inhabiting the Gulf of St. Lawrence, Canada. We provide evidence that the circulating microbiome DNA (cmDNA) is driven by both species-specific and environmental factors. More specifically, we found that the circulating microbiome signatures are species specific and vary according to sex, size, temperature, condition factor, and geographical localization. Overall, our study provides a novel approach for the detection of dysbiotic signatures and the risk of disease in wild fish populations for fisheries management, most notably in the context of climate change.
... This opens a promising avenue of research; by cataloging the observed changes in the microbiome when a host is exposed to a specific anesthetic drug, researchers can propose a causal relationship between the microbiome population and activity shifts with the introduction of a particular anesthetic drug. This approach to precision medicine can easily transition from bench to bedside, utilizing microgeonomics with special attention to the cellfree DNA as shown by teams in China (6) and with newer technologies similar in nature to the Karius, currently used in diagnostics (7,8), and other methods such as the one reported by Whittle et al (9) to identify the populations that inhabit one's microbiome by utilizing advanced algorithms and soft AI. This approach to personalized anesthesia can solve three prevalent phenomena within the field, including unpredictable anesthetic emergencies and side effects, the ability of the trained anesthesiologist to select the best possible cocktail of anesthetic drugs to avoid postoperative sequelae, and the possibility of allowing a better understanding and utilization of drugs employed in pain management and the origin of complex pain symptoms in the first place (3)(4)(5). ...
Article
Full-text available
Dear editor, One of the many developing interests in the medical field is the utilization of the human microbiome, which is a complex system of thousands of microorganisms within various body systems, whose population is unique to the individual. Much of this hype is secondary to the work performed under the aptly named Human Microbiome Project (1). The human microbiome grants an individual, unique qualities ranging from specific inflammatory markers to the development of neurological processes. These qualities are adaptable and respond to numerous types of external and internal stimuli. Examples of these changes can be witnessed when the host is exposed to chronic pain stimuli - neurological, visceral, or otherwise. It has been documented that pain signals alter microbiome metabolites, and the subsequent treatment of that pain further induces changes within the microbiome. It is suggested, then, that the gut microbiome is a dynamic population that is constantly changing within a person, and thus “anybody’s” microbiome can be entirely different from the next. The field of anesthesiology may be next to utilize the human microbiome.
... Moreover, several studies have suggested the existence of tissue microbiota either in humans or in mice [16][17][18][19]. The 16S rRNA gene signature was also demonstrated in the blood of healthy humans (primarily leukocyte and platelet fractions) [20] or patients [21,22] as well as in the circulation of animals [23][24][25]. These key factors illustrate the crosstalk line between the gut microbiota, circulation, and tissues [26], that is, the gut microbiota enter into the circulation through leakage and locate into tissues and change into tissue microbiota/tumor type-speci c intracellular bacteria. ...
Preprint
Full-text available
The tumor and tissue microbiomes of human beings have recently been investigated. Gut permeability is known as a possible resource for the positive detection of tissue bacteria. Herein, we report that bacteria were detected in high abundance in the hepatocytes of healthy rats, and that they were shared with the gut microbiota to an extent. We assessed male Sprague Dawley (SD) rats for the 16S ribosomal ribonucleic acid (rRNA) gene. After rats were sacrificed by blood drainage from the portal vein, we extracted total deoxyribonucleic acid (DNA) from their ileal and colonic contents and liver tissues. The V3–V4 region of the 16S rRNA gene was amplified by polymerase chain reaction (PCR) and sequenced using an Illumina HiSeq 2500 platform. Sequences were assigned taxonomically by the SILVA database. We also detected bacterial lipopolysaccharide (LPS) and lipoteichoic acid (LTA) in situ using immunofluorescence (IF) and western blotting and the 16S rRNA gene using fluorescent in situ hybridization (FISH). In the livers of six rats, we detected 54,867.50 ± 6450.03 effective tags of the 16S rRNA gene and clustered them into 1003 kinds of operational taxonomic units (OTUs; 805.67 ± 70.14, 729–893). Individuals showed conservation of bacterial richness, abundance, and evenness. LPS and 16S rRNA gene were detected in the nuclei of hepatocytes. The main function composition of the genomes of the annotated bacteria was correlated with metabolism (79.92 ± 0.24%). Gram negativity was about 1.6 times higher than gram positivity. Liver bacteria were shared with both the small and large intestines but showed significantly higher richness, evenness, and β-diversity results showed that the liver microbiota exhibited significantly higher similarity than the small and large intestines ( P < 0.05). The liver microbiota were hidden intracellular inhabitants in healthy rat livers and were shared with the gut microbiota.
Article
Full-text available
Background Characteristics of the blood microbiota among adult patients with community-acquired sepsis are poorly understood. Our aim was to analyze the composition of blood microbiota in adult patients with community-acquired sepsis, and correlate changes with non-septic control patients. Methods A prospective observational study was carried out by including adult patients hospitalized for community-acquired sepsis at our center between January and November 2019, by random selection from a pool of eligible patients. Study inclusion was done on the day of sepsis diagnosis. Community acquisition was ascertained by a priori exclusion criteria; sepsis was defined according to the SEPSIS-3 definitions. Each included patient was matched with non-septic control patients by age and gender in a 1:1 fashion enrolled from the general population. Conventional culturing with BacT/ALERT system and 16S rRNA microbiota analysis were performed from blood samples taken in a same time from a patient. Abundance data was analyzed by the CosmosID HUB Microbiome software. Results Altogether, 13 hospitalized patients were included, 6/13 (46.2%) with sepsis and 7/13 (53.8%) with septic shock at diagnosis. The most prevalent etiopathogen isolated from blood cultures was Escherichia coli , patients mostly had intraabdominal septic source. At day 28, all-cause mortality was 15.4% (2/13). Compared to non-septic control patients, a relative scarcity of Faecalibacterium , Blautia, Coprococcus and Roseburia genera, with an abundance of Enhydrobacter , Pseudomonas and Micrococcus genera was observed among septic patients. Relative differences between septic vs. non-septic patients were more obvious at the phylum level, mainly driven by Firmicutes (25.7% vs. 63.1%; p<0.01) and Proteobacteria (36.9% vs. 16.6%; p<0.01). The alpha diversity, quantified by the Chao1 index showed statistically significant difference between septic vs. non-septic patients (126 ± 51 vs. 66 ± 26; p<0.01). The Bray-Curtis beta diversity, reported by principal coordinate analysis of total hit frequencies, revealed 2 potentially separate clusters among septic vs. non-septic patients. Conclusion In adult patients with community-acquired sepsis, specific changes in the composition and abundance of blood microbiota could be detected by 16S rRNA metagenome sequencing, compared to non-septic control patients. Traditional blood culture results only partially correlate with microbiota test results.
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Emerging evidence revealed that the blood microbiota plays a role in several non-communicable diseases, including cardiovascular disease. However, the role of circulating microbes in atherosclerosis remains understudied. To test this hypothesis, we performed this study to investigate the microbial profile in the blood of Chines atherosclerosis volunteers. A total of seventy Acute Coronary Syndrome patients, seventy Chronic Coronary Syndrome patients, and seventy healthy individuals were examined using high-throughput Illumina Novaseq targeting the V3-V4 regions of the 16S rRNA gene. The relationship between atherosclerosis and blood microbiome, clinical variables, and their functional pathways were also investigated. Our study observed significantly higher alpha diversity indices (Chao1, p = 0.001, and Shannon, p = 0.004) in the acute coronary syndrome group compared with chronic coronary syndrome and healthy group, although a significantly lower alpha diversity was observed in the chronic coronary syndrome compared to acute coronary syndrome and healthy group. Beta diversity based on principal coordinate analysis demonstrated a major separation among the three groups. In addition, using linear discriminant analysis, a significant distinct taxon such as Actinobacteria _ phylum, and Staphylococcus_ genus in the healthy group; Firmicutes_ phylum, and Lactobacillus_ genus in the chronic coronary syndrome group, and Proteobacteria and Acidobacteriota _ phyla in acute coronary syndrome group were observed among three groups. Clusters of Orthologous Genes grouped and Kyoto Encyclopedia of Genes and Genomes pathways suggested a significant variation among all groups (p < 0.05). The blood microbiota analysis provides potential biomarkers for the detection of coronary syndromes in this population.
Preprint
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Background An increasing number of research studies observe that human blood is not a completely sterile environment and has its own representative microbiome. This study aimed to determine the blood microbiome's composition, potential origin, and dynamics in humans.ResultsTo detect the origin of exogenous bacterial nucleic acids in the blood, we determined taxonomic composition based on 16S rRNA gene analysis in samples obtained from skin, vaginal, oral, and faecal swabs along with whole blood samples in a group of 10 volunteers. We observed a presence of bacterial DNA with variable taxonomic composition in all blood samples strongly dominated by members of the Pseudomonas genus. In addition, we detected identical bacterial Amplicon Sequence Variants (ASV) that overlapped between blood and other locations in all participants. Overall, 27.4% median of all ASVs from blood were also found in various locations, with the highest number found in the samples collected from skin swabs. Overall, 25.3% of the ASV found in blood overlapped between the baseline and three-month blood samples, indicating the blood microbiome's relative stability.Conclusions We have presented for the first time a remarkable overlap between the bacterial composition of blood and other locations of the same individuals, allowing us to propose the skin microbiota as the primary source of blood-related exogenous DNA. Furthermore, our results add a piece of new knowledge on the stability of the blood microbiome, providing the basis for future studies to identify the potential effect of the blood microbiome on the phenotype or disease.
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Abstract Background: On the analogy of the non-pathogenic microbiota found in oral cavity, skin and gastrointestinal tract, existence of blood microbiota was confirmed by DNA sequencing, but never deeply characterized. Hypothesis for the existence of dormant blood microbiota in healthy humans have been arisen and single species have been isolated. The aim of our study was to resuscitate and investigate the biodiversity of bacterial and fungal dormant blood microbiota in healthy individuals by blood culturing and NGS DNA sequencing. Results: Twenty eight blood samples of healthy individuals, seven for each blood type, were studied. Several culture media were tested. Blood microbiota resuscitation was performed in BHI broth supplemented with vitamin K 1 mg/ml, 2% sucrose, 0.25% sodium citrate and 0.2% yeastolate at 43˚C for 72 h. All tested blood samples were culture positive, as confirmed by Gram staining and TEM. TEM images demonstrated well defined cell structures. Analysis for bacterial and eukaryotic species was performed by 16S rRNA and ITS2 targeted sequencing. The obtained sequences were clustered (≥97% identity) in Operational Taxonomic Units (OTUs). Among cultured and uncultured samples we identified OTUs similarity with 47 bacterial orders belonging to 15 phyla and 39 fungi orders blonging to 2 phyla. For the first time we demonstrated isolation and sequencing identification of fungal blood microbiota in healthy individuals. Blood-group differences were identified among the bacterial microbiome compositions. Conclusion: The dormant blood microbiome is innate of the healthy individuals. Interventional strategies to bind the host blood microbiome with the states of health and disease remain an unmet research goal.
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The role of the human microbiome in health and disease is increasingly appreciated. We studied the composition of microbial communities present in blood across 192 individuals, including healthy controls and patients with three disorders affecting the brain: schizophrenia, amyotrophic lateral sclerosis, and bipolar disorder. By using high-quality unmapped RNA sequencing reads as candidate microbial reads, we performed profiling of microbial transcripts detected in whole blood. We were able to detect a wide range of bacterial and archaeal phyla in blood. Interestingly, we observed an increased microbial diversity in schizophrenia patients compared to the three other groups. We replicated this finding in an independent schizophrenia case-control cohort. This increased diversity is inversely correlated with estimated cell abundance of a subpopulation of CD8+ memory T cells in healthy controls, supporting a link between microbial products found in blood, immunity and schizophrenia.
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Infectious complications are a leading cause of death for patients with severe acute pancreatitis (SAP). Yet, our knowledge about details of the blood microbial landscape in SAP patients remains limited. Recently, some studies have reported that the peripheral circulation harbors a diverse bacterial community in healthy and septic subjects. The objective of this study was to examine the presence of the blood bacterial microbiome in SAP patients and its potential role in the development of infectious complications. Here we conducted a prospective observational study on a cohort of 50 SAP patients and 12 healthy subjects to profile the bacterial composition in the blood. The patients were subgrouped into uninfected (n = 17), infected (n = 16), and septic (n = 17) cases. Applying 16S rDNA-based next-generation sequencing technique, we investigated blood and neutrophil-associated microbiomes in SAP patients, and assessed their connections with immunological alterations. Based on the sequencing data, a diverse bacterial microbiota was found in peripheral blood and neutrophils from the healthy and SAP subjects. As compared to healthy controls, the blood and neutrophil-associated microbiomes in the patients were significantly altered, with an expansion in Bacteroidetes and Firmicutes as well as a decrease in Actinobacteria. Variations in the microbiome composition in patients were associated with immunological disorders, including altered lymphocyte subgroups, elevated levels of serum cytokines and altered proteomic profiles of neutrophils. However, no significant compositional difference was observed between the patient subgroups, implying that the microbiota alterations might not be linked to presence/absence of infectious complications in SAP. Together, we present an initial description of the blood and neutrophil-associated bacterial profiles in SAP patients, offering novel evidence for the existence of the blood microbiome. Identification of the blood microbiome provides novel insights into characteristics and diagnostics of bacteremia in the patients. Further study is required to assess the possible implications of the blood microbiome in health and diseases.
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Although human blood is believed to be a sterile environment, recent studies suggest that pleomorphic bacteria exist in the blood of healthy humans. These studies have led to the development of “live-blood analysis,” a technique used by alternative medicine practitioners to diagnose various human conditions, including allergies, cancer, cardiovascular disease and septicemia. We show here that bacteria-like vesicles and refringent particles form in healthy human blood observed under dark-field microscopy. These structures gradually increase in number during incubation and show morphologies reminiscent of cells undergoing division. Based on lipid analysis and Western blotting, we show that the bacteria-like entities consist of membrane vesicles containing serum and exosome proteins, including albumin, fetuin-A, apolipoprotein-A1, alkaline phosphatase, TNFR1 and CD63. In contrast, the refringent particles represent protein aggregates that contain several blood proteins. 16S rDNA PCR analysis reveals the presence of bacterial DNA in incubated blood samples but also in negative controls, indicating that the amplified sequences represent contaminants. These results suggest that the bacteria-like vesicles and refringent particles observed in human blood represent non-living membrane vesicles and protein aggregates derived from blood. The phenomena observed during live-blood analysis are therefore consistent with time-dependent decay of cells and body fluids during incubation ex vivo.
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Background: Metritis is an inflammatory disease of the uterus caused by bacterial infection, particularly Bacteroides, Porphyromonas, and Fusobacterium. Bacteria from the environment, feces, or vagina are believed to be the only sources of uterine contamination. Blood seeps into the uterus after calving; therefore, we hypothesized that blood could also be a seeding source of uterine bacteria. Herein, we compared bacterial communities from blood, feces, and uterine samples from the same cows at 0 and 2 days postpartum using deep sequencing and qPCR. The vaginal microbiome 7 days before calving was also compared. Results: There was a unique structure of bacterial communities by sample type. Principal coordinate analysis revealed two distinct clusters for blood and feces, whereas vaginal and uterine bacterial communities were more scattered, indicating greater variability. Cluster analysis indicated that uterine bacterial communities were more similar to fecal bacterial communities than vaginal and blood bacterial communities. Nonetheless, there were core genera shared by all blood, feces, vaginal, and uterine samples. Major uterine pathogens such as Bacteroides, Porphyromonas, and Fusobacterium were part of the core genera in blood, feces, and vagina. Other uterine pathogens such as Prevotella and Helcococcus were not part of the core genera in vaginal samples. In addition, uterine pathogens showed a strong and significant interaction with each other in the network of blood microbiota, but not in feces or vagina. These microbial interactions in blood may be an important component of disease etiology. The copy number of total bacteria in blood and uterus was correlated; the same did not occur in other sites. Bacteroides heparinolyticus was more abundant in the uterus on day 0, and both B. heparinolyticus and Fusobacterium necrophorum were more abundant in the uterus than in the blood and feces on day 2. This indicates that B. heparinolyticus has a tropism for the uterus, whereas both pathogens thrive in the uterine environment early postpartum. Conclusions: Blood harbored a unique microbiome that contained the main uterine pathogens such as Bacteroides, Porphyromonas, and Fusobacterium. The presence of these pathogens in blood shortly after calving shows the feasibility of hematogenous spread of uterine pathogens in cows.
Preprint
Pavian is a web application for exploring metagenomics classification results, with a special focus on infectious disease diagnosis. Pinpointing pathogens in metagenomics classification results is often complicated by host and laboratory contaminants as well as many non-pathogenic microbiota. With Pavian, researchers can analyze, display and transform results from the Kraken and Centrifuge classifiers using interactive tables, heatmaps and flow diagrams. Pavian also provides an alignment viewer for validation of matches to a particular genome. Availability and implementation Pavian is implemented in the R language and based on the Shiny framework. It can be hosted on Windows, Mac OS X and Linux systems, and used with any contemporary web browser. It is freely available under a GPL-3 license from http://github.com/fbreitwieser/pavian . Furthermore a Docker image is provided at https://hub.docker.com/r/florianbw/pavian . Contact fbreitw1@jhu.edu Supplementary information Supplementary data is available at Bioinformatics online.
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Background: Circulating RNA in plasma/serum is an emerging field for noninvasive molecular diagnosis. Because RNA is widely thought to be labile in the circulation, we investigated the stability and various preanalytical factors that may affect RNA concentrations in blood specimens. Methods: Blood samples were collected from 65 healthy volunteers. The effects of two preanalytical variables were studied: (a) time delay in processing of EDTA blood and clotted blood after venesection, and (b) freezing and thawing of plasma and serum. The lability of free added RNA in plasma was also investigated. Plasma/serum RNA was measured by a real-time quantitative reverse transcription-PCR assay for glyceraldehyde 3-phosphate dehydrogenase mRNA, whereas DNA was measured by a real-time quantitative PCR assay for the β-globin gene. Results: No significant difference was found for plasma RNA concentrations obtained from uncentrifuged EDTA blood that had been left at 4 °C for 0, 6, and 24 h (P =0.182). On the other hand, the serum RNA concentrations increased significantly over 24 h when uncentrifuged clotted blood was stored at 4 °C (P <0.05). In comparison, >99% of the free added RNA could no longer be amplified after incubation in plasma for 15 s. Never-frozen plasma, freeze-thawed plasma, and thawed plasma left at room temperature for 1 h showed no significant differences in RNA concentration (P =0.465). No significant difference was observed for freeze-thawed serum (P = 0.430). Conclusions: Plasma RNA is stable in uncentrifuged EDTA blood stored at 4 °C, but to obtain a stable serum RNA concentration, uncentrifuged clotted blood should be stored at 4 °C and processed within 6 h. A single freeze/thaw cycle produces no significant effect on the RNA concentration of plasma or serum.
Preprint
The term microbiome describes the genetic material encoding the various microbial populations that inhabit our body. Whilst colonisation of various body niches (e.g. the gut) by dynamic communities of microorganisms is now universally accepted, the existence of microbial populations in other classically sterile locations, including the blood, is a relatively new concept. The presence of bacteria-specific DNA in the blood has been reported in the literature for some time, yet the true origin of this is still the subject of much deliberation. The aim of this study was to provide a comprehensive description of the human blood microbiome using a range of complementary molecular and classical microbiological techniques. DNA-level analyses involved the amplification and sequencing of the 16S rDNA gene. RNA-level analyses were based upon the de novo assembly of unmapped mRNA reads. Molecular studies were complemented by viability data from classical aerobic and anaerobic microbial culture experiments. At the phylum level, the blood microbiome was predominated by Proteobacteria, Actinobacteria, Firmicutes and Bacteroidetes. The key phyla detected were consistent irrespective of molecular method (DNA vs RNA), and consistent with the results of other published studies. In silico comparison of our data with that of the Human Microbiome Project revealed that members of the blood microbiome were most likely to have originated from the oral or skin communities. To our surprise, aerobic and anaerobic cultures were positive in eight of out the ten donor samples investigated, and we reflect upon their source. Our data provide further evidence of a core blood microbiome, and provide insight into the potential source of the bacterial DNA / RNA detected in the blood. Further, data reveal the importance of robust experimental procedures, and identify areas for future consideration.
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From a historical perspective, intriguing assumptions about unknown "live units" in human blood have attracted the attention of researchers, reflecting their desire to define a new class of microorganisms. Thus, the concept of "blood microbiota" brings about many questions about the nature, origin, and biological significance of the "unusual microbial cohabitants" in human blood. In contrast to current views that bloodstream in healthy humans is sterile, the hypothesis about the existence of microbes as L-forms (cell wall deficient bacteria) in human blood has evolved on the basis of known facts about their unique biology, as observed in our studies and those of other authors. Recently, we reported that bacterial L-forms persist in the human blood and that filterable, self-replicating bodies with a virus-like size of 100 nm are able to cross the maternal-fetal barrier by vertically transmitted pathway, then enter fetus blood circulation and colonize newborns. Subjects discussed here include the following: Is the existence of L-form bacteria in human blood a natural phenomenon? Are L-form bacteria commensal cohabitants in the human body? Since blood is an unfavorable compartment for the classical bacteria and their propagation, how do L-forms survive in blood circulation? How does L-form microbiota in blood influence the host immune system and contribute to systemic inflammatory, autoimmune, and tumor diseases? The current commentary presents the topic of "human microbiota and L-form bacteria" in its microcosm. It contains details of the hypothesis, supporting evidence and important implications.