Đề ôn thi thử môn hóa (853)

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7. Becattini S, Latorre D, Mele F, et al. T cell immunity. Functional
heterogeneity of human memory CD4(1) T cell clones primed by
pathogens or vaccines. Science. 2015;347:400-406.
8. Geginat J, Paroni M, Maglie S, et al. Plasticity of human CD4 T cell
subsets. Front Immunol. 2014;5:630.
9. Mai J, Wang H, Yang XF. Th 17 cells interplay with Foxp31 Tregs
in regulation of inflammation and autoimmunity. Front Biosci.
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10. Romagnani S, Maggi E, Liotta F, Cosmi L, Annunziato F. Properties
and origin of human Th17 cells. Mol Immunol. 2009;47:3-7.
11. Ueno H, Banchereau J, Vinuesa CG. Pathophysiology of T follicular
helper cells in humans and mice. Nat Immunol. 2015;16:142-152.
12. Pan HF, Leng RX, Li XP, Guo Zheng S, Ye DQ. Targeting T-helper
9 cells and interleukin-9 in autoimmune diseases. Cytokine Growth

Factor Rev. 2013;24:515-522.
13. Kaplan MH, Hufford MM, Olson MR. The development and in
vivo function of T helper 9 cells. Nat Rev Immunol. 2015;15:295307.
14. Hein F, Massin F, Cravoisy-Popovic A, et al. The relationship between CD4+CD25+CD1272regulatory T cells and inflammatory
response and outcome during shock states. Crit Care. 2010;14:R19.
15. Muszynski JA, Nofziger R, Greathouse K, et al. Early adaptive immune suppression in children with septic shock: a prospective observational study. Crit Care. 2014;18:R145.
16. Venet F, Chung CS, Kherouf H, et al. Increased circulating
regulatory T cells (CD4(1)CD25 (1)CD127 (-)) contribute to
lymphocyte anergy in septic shock patients. Intensive Care Med. 2009;
35:678-686.
17. Venet F, Pachot A, Debard AL, et al. Increased percentage of
CD41CD251 regulatory T cells during septic shock is due to the
decrease of CD41CD25- lymphocytes. Crit Care Med. 2004;32:
2329-2331.
18. Wu HP, Chung K, Lin CY, Jiang BY, Chuang DY, Liu YC. Associations of T helper 1, 2, 17 and regulatory T lymphocytes with mortality in severe sepsis. Inflamm Res. 2013;62:751-763.
19. Fahl SP, Coffey F, Wiest DL. Origins of gammadelta T cell effector
subsets: a riddle wrapped in an enigma. J Immunol. 2014;193:42894294.

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associated with repression of adaptive immunity gene programs in
pediatric septic shock. Am J Respir Crit Care Med. 2014;189:940946.
28. Wong HR, Freishtat RJ, Monaco M, et al. Leukocyte subset-derived
genomewide expression profiles in pediatric septic shock. Pediatr
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30. Hotchkiss RS, Tinsley KW, Swanson PE, et al. Sepsis-induced
apoptosis causes progressive profound depletion of B and CD41
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e2

Abstract: A well-coordinated and functioning immune response
is vital to maintaining health and to recovering from critical
illness. As such, it is important for the pediatric intensivist to
understand elements of both the innate and adaptive immune
systems. This chapter reviews development and function of
the cellular elements of adaptive immunity, adaptive immune

activation, crosstalk between innate and adaptive immune responses, and clinical topics that are related to adaptive immunity
and are of particular relevance to pediatric critical care medicine.
Key words: T lymphocyte, B lymphocyte, antibody, humoral
immunity, cell-mediated immunity


102
Critical Illness and the Microbiome
RAFAEL G. RAMOS-JIMENEZ, DENNIS SIMON, AND MICHAEL J. MOROWITZ

•



The term microbiome was first used to describe the collective genome of a microbial ecosystem in 2001.1,2 By 2007, the National
Institutes of Health (NIH) had launched the first phase of the
Human Microbiome Project (HMP) with the objective of describing the bacterial communities of healthy individuals.1,3 Although these initial studies showed substantial interindividual
variation at lower phylogenetic levels, such as genus and species,
the phyla Bacteroidetes and Firmicutes clearly emerged as dominant in the healthy gut, and Actinobacteria and Firmicutes were
shown to be the dominant skin phyla.4 The clear dominance of a
limited set of phyla (and the absence of most others) colonizing
human body niches highlights the long nonrandom coevolution
between humans and bacteria.5
Interestingly, the wide taxonomic variation seen in the gut
microbiome of healthy individuals disappears at the gene level.
Even during the unstable period of infancy, gut microbes maintain a relatively constant abundance of genes that encode for
specific metabolic pathways.6–9 This genetic “core” can be attained
by different combinations of taxa, which explains why different
taxonomic configurations are all compatible with health and the
consistent association between taxonomic diversity and a healthy
microbiome.10 The important insight provided by genomic studies was that the functional diversity that allows gut microbes to
adapt to environmental, physiologic, and nutritional changes is
found at the genomic level, not the taxonomic level. The collective genome of the community, known as a metagenome, is what
maintains ecologic stability and appropriate nutrient cycling.11,12
At present, the study of microbiome science is moving from
correlation to causation.13–18 The current approach to microbiome research integrates taxonomic, genomic, proteomic, physiologic, and metabolic data to allow contextualization of microbial
communities, mechanistic descriptions, and biomarker identification. In 2014, the second phase of the HMP, known as the integrative HMP (iHMP), was launched by the NIH with the goal of
describing the microbiome in pregnancy, inflammatory bowel
1208

•



Like all organisms, humans have evolved in concert with microbes that serve numerous physiologic and immune functions
during normal development and homeostasis.
Critical illness in both children and adults has been associated
with profound changes in the microbiome at numerous body
sites.

•



•



PEARLS
The short- and long-term clinical consequences of these
changes in the microbiome have not been clearly elucidated.
Despite huge leaps in our understanding of host microbiome
interactions during health and disease, the human microbiome’s diagnostic, prognostic, and therapeutic potential is yet to
be realized.

disease (IBD), and type 2 diabetes—three important conditions
linked previously to aberrant patterns of microbial colonization.
The initial results of the iHMP have already refined and expanded
our understanding of host-microbe relationships in health and
disease, moving microbiome science further from correlation and

closer to causation.3

General Concepts in the Field
of Microbiome Science
Commensal, Pathogenic, and Keystone Species
The term commensal describes an ecologic relation between two
organisms in which the commensal benefits and the host is neither benefited nor harmed.19 Our understanding of the human
microbiome suggests that bacteria have a mutualistic relationship
with us rather than a commensal one. That is, both the bacteria
and their human host benefit from the relationship. On the other
hand, pathogenic species are those that, when present in a host, can
cause disease. However, many studies show that these distinctions
are fluid in the context of the human microbiome, where nutrient
availability, presence of pathogenicity islands, and inflammation
can turn mutualists into pathogens.12,20–22 Another important
concept is that of keystone species, which are “highly connected
taxa that individually or in a guild exert a considerable influence
on microbiome structure and functioning irrespective of their
abundance across space and time.”23

Site Specificity
The human body provides microorganisms with hugely divergent
ecosystems to colonize. These ecosystems range from the anaerobic and nutrient-rich gut lumen to the aerobic but nutrientdepleted stratified squamous epithelia of the skin. The different
habitats select for different microbes leading to site specificity,


CHAPTER 102  Critical Illness and the Microbiome

which is the well-described observation that microbial community membership varies predictably depending on the sampled
body location.3,4,24 Although not yet proven, it has been postulated that loss of site specificity may portend worse outcomes in

both critically ill children and adults.22,25

Dysbiosis
The term dysbiosis has been loosely applied in the literature to any
deviation from a healthy microbiome, especially when this deviation is associated with disease.22,26,27 These shifts have been associated with changes in diet, disease states, antibiotic use, surgical
trauma, and many other insults.20 In the context of critical illness,
a useful definition of dysbiosis is “a state of microbial organ dysfunction, a condition in which the gut-associated microbial community becomes a liability because the host no longer maintains
proper control over the ecosystem.”28,29 This dysfunction is most
consistently associated with a shift from obligate to facultative
anaerobes in the gut.28
Although many ecologic perturbations are transient, the dysbiotic state persists when an insult is chronic, such as in IBD, or
severe enough in acute conditions to cause a loss of keystone species.30–33 This persistent dysbiosis is further exacerbated by physiologic insults accompanying acute critical illness that increase
expression of virulence factors even among commensal organisms.11,12 The persistence of these dysfunctional communities has
been associated with immunologic dysfunction, increased inflammation, and increased epithelial permeability, suggesting a role for
the microbiome as both a cause and/or a consequence of critical
illness (Fig. 102.1).33–36 As discussed later, it is not yet known
whether intensive care unit (ICU)–related dysbiosis resolves over

Healthy

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time in patients who experience clinical improvement and whether
microbiome-targeted therapies to reverse dysbiosis can hasten
patient recovery or improve outcomes.
This chapter focuses on the bacterial component of the human
microbiome. However, it is important to note that the human
microbiome also consists of viral, fungal, and protozoan communities that are currently harder to study for technical reasons.37,38
For example, study of the human virome, which includes viruses
that infect human cells as well as other microbes within the body

(e.g., bacteriophages), is limited because (1) viruses do not contain a conserved genomic region, such as the 16S gene in bacteria;
and (2) many viruses are not included in viral databases.39 Newer
techniques (see later discussion on metagenomic sequencing), although more expensive than amplicon sequencing, have overcome several barriers to studying nonbacterial communities in the
human microbiome and revealed increasingly complex interactions within the microbiome and with the host in healthy and
diseased states.

Studying the Microbiome
Historically, clinical microbiology has relied heavily on the ability
to cultivate pathogens from patient samples sent to clinical microbiology laboratories. This approach works well for a sample such
as cerebrospinal fluid, which should be sterile but in some circumstances may contain a heavy burden of a single causative pathogen. However, this approach is less effective in characterizing
mixed communities of organisms—especially in samples such as
stool or sputum, with high bacterial density even in the absence
of infection. One reason for this problem is that many or most
organisms within the human microbiome cannot be cultivated for

Critically ill
Lung microbiota
dysbiosis

Effective elimination
of pathogens

Difficulty to
eliminate pathogens

Immunomodulation

Dysregulated
immunomodulation

Priming of immune system through
bacterial ligands and metabolites

Intestinal microbiota dysbiosis due
to critical illness and given therapies,
such as antibiotics

Intestinal bacteria give protection
against local invasion of pathogens

Intestine loses protection
against local invasion of pathogens

• Fig. 102.1  ​The gut and lung microbiota in critical illness. Healthy microbial communities in the human
gut and lung protect against colonization by pathogens. In critically ill patients with dysbiotic microbial
communities, these protective responses are compromised. (From Wolff NS, Hugenholtz F, Wiersing WJ.
The emerging role of the microbiota in the ICU. Crit Care. 2018;22.)


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S E C T I O N X I   Pediatric Critical Care: Immunity and Infection

TABLE
102.1 Schematic Overview of a Compartmentalized Host-Microbe Metabolic Model Setup

Data Type

(Meta)genomics

Meta(proteomics),
Meta(transcriptomics)

Input data

16S rRNA data Metagenomic
reads Host genetics

Affected constraints

Microbiome composition and
relative abundances Host
phenotype

Metabolomics

Nutrition

Gene expression levels
Protein levels

Media metabolites
Stool metabolites
Blood metabolites
Urine metabolites

Food frequency questionnaires
Standardized diets
Growth media

Active metabolic pathways in
individual microbes and
host reconstruction

Output metabolites
Metabolite secretion into
body fluids

Input metabolites

technical reasons.40 This may change with time with new knowledge about the metabolic and nutritional requirements of humanassociated microbes. It is important for clinicians and scientists
alike to realize that culture-dependent and culture-independent
studies of the microbiota each have advantages and disadvantages.
The ability to complement or bypass laboratory culture in the
study of the human microbiome has improved dramatically as a
result of three recent scientific advances: high-throughput nucleic acid sequencing, the use of gene sequences encoding the
16S ribosomal subunit to enable taxonomic assignments, and the
development of robust bioinformatic methods to analyze and
interpret these results. Similar to -omics studies of the human
genome, culture-independent studies of the microbiome can
be categorized into several categories depending on the input
variables of the experiment (Table 102.1), for example, DNA
or RNA.
Bacterial profiling of microbiome samples is commonly based
on analysis of a 1.5-Kbp gene that encodes the subunit of bacterial ribosomes. The nine hypervariable regions (V1–V9) of this
gene are highly conserved among bacterial phyla but variable at
lower taxonomic levels, making it an effective phylogenetic
marker.42,43 16S rRNA gene sequencing results typically contain
genes from numerous organisms, which can be identified using
reference databases such as the Ribosomal Database Project

(myRDP) or Silva. This process is called closed reference operational taxonomic unit picking.44,45 In the case of the human gut
microbiome, for example, extensive reference databases exist that
are reliable and provide good specificity and sensitivity.14 In samples without extensive reference databases, such as respiratory
samples, more challenging bioinformatic methods may be required to identify the bacterial composition present within the
samples.46,47
Once taxonomic assignments have been made, diversity measures can be calculated. The most commonly used diversity measures are alpha diversity and beta diversity. Alpha diversity measures the number of taxa within an environment, while beta
diversity quantifies differences between environments. In other
words, alpha diversity describes a single population, while beta
diversity describes two or more populations.47–49 In summary, the
steps of a typical taxonomic analysis are extraction of DNA from
a sample (stool, saliva, etc.), targeted or untargeted (see later discussion) sequencing of microbial DNA, taxonomy assignment,
and community analyses of diversity.
Whole-genome sequencing, or metagenomics, is another commonly used technique to study the microbiome but is more costly
and labor intensive. This technique consists of sequencing and
characterizing all of the microbial DNA present within a sample.

Whereas 16S rRNA gene sequences are effective in profiling community membership, metagenomic sequencing studies are unbiased analyses of all genetic information present within microbial
communities. In theory, metagenomic studies are not restricted to
bacteria and offer the potential not only to identify which organisms are present but also to catalog all genes present, to predict
their metabolic or virulence potential, and, in some cases, assemble entire microbial genomes.50,51
Complementary -omics studies build on studies of DNA content to characterize the RNA, protein, and/or metabolites present
within a given sample.

Development of the Microbiome in Children
Prior to delivery, the fetus is considered to be sterile or near-sterile.52 Cesarean and vaginal delivery each expose the newborn to a
significant burden of bacteria; predominantly skin and oral flora
in the case of cesarean delivery and vaginal and intestinal flora
such as Enterobacteriaceae and Bacteroidaceae in the case of vaginal
delivery. Controversy exists as to whether the mode of delivery
confers lasting changes in bacterial colonization. However, no

functional differences of the microbiome have been observed
between infants born by vaginal or cesarean delivery. Recent
evidence describing amniotic, placental, and meconium microbiomes suggests that maternal-fetal microbiota transfer may also
occur.53
Site specificity of the microbiome has been observed at as early
as 6 weeks of life.54 At this age, stool, oral, and skin microbiota
cluster distinctly and are enriched with characteristic microbiota—
for example, Streptococcus in oral samples, Staphylococcus and
Corynebacterium in skin samples, and Bacteroides in stool samples.
Diet significantly influences the development of the infant microbiome. Multiple studies have demonstrated differences in gut
microbiota between breastfed and formula-fed infants.55 Breastfed
infants receive significant bacterial exposure from breastmilk,
which contains high quantities of Lactobacillus and Bifidobacterium spp. These bacteria are able to synthesize compounds with
antimicrobial effects against pathogenic bacteria and which assist
digestion of human milk. Formula-fed infants have a higher
prevalence of Clostridium and Roseburia spp. in their gut and
overall have reduced alpha- and beta-diversity relative to breastfed
children.56
Following the introduction of cereals and other solid foods, a
rapid expansion of diversity occurs in the infant gut with an increase in relative abundance of obligate anaerobic bacteria, including Bacteroidetes and Firmicutes. By approximately 2 to 3 years
of age, the microbiome of children resembles that of adults and