Physiological Reports. 2019;7:e14313. 
 
  |  1 of 7
https://doi.org/10.14814/phy2.14313
wileyonlinelibrary.com/journal/phy2
1 | 
INTRODUCTION
In 2007 the National Institutes of Health launched the Human 
Microbiome Project (HMP), an interdisciplinary research 
initiative seeking to characterize the contribution of human 
gut microbiota to health and disease (Turnbaugh et al., 
2007). Subsequent findings have demonstrated compelling 
relationships between human gut microbiome composition 
and many leading causes of death worldwide including car-
diovascular disease (Wang et al., 2011), diabetes (Larsen et 
al., 2010), and cancer (Ahn et al., 2013). Although the gut 
microbiome is suggested to exhibit exceptional plasticity 
(Gomez et al., 2019), a detailed understanding of the fac-
tors determining human microbiome assembly is lacking 
(Relman, 2015).
DOI: 10.14814/phy2.14313  
O R I G I N A L  R E S E A R C H
Rapid gut microbiome changes in a world-class ultramarathon 
runner
Gregory J. Grosicki1
 |   Ryan P. Durk2 |   James R. Bagley2
This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original 
work is properly cited.
© 2019 The Authors. Physiological Reports published by Wiley Periodicals, Inc. on behalf of The Physiological Society and the American Physiological Society.
1Biodynamics and Human Performance 
Center, Georgia Southern University, 
Savannah, Georgia
2San Francisco State University, San 
Francisco, California
Correspondence
Gregory J. Grosicki, Biodynamics and 
Human Performance Center, Georgia 
Southern University (Armstrong Campus), 
11935 Abercorn Street, Savannah, GA, 
31419.
Email: ggrosicki@georgiasouthern.edu
Funding information
Rossi Family Foundation
Abstract
The human gut microbiome is a dynamic ecosystem with prolific health connotations. 
Physical activity is emerging as a potent regulator of human microbiome composition. 
This study examined changes in the gut microbiome of a world-class ultramarathon 
runner before and after competing in the Western States Endurance Run (WSER), a 
163 km mountain footrace. Anthropometrics and body composition were assessed 
and the ultramarathoner's submaximal and maximal performance profiles were eval-
uated. Gut microbiome analyses were performed at four time-points: 21 weeks and 
2 weeks before and 2 hours and 10 days after WSER. Aerobic power (VO2max) 
was 4.24 L/min (66.7 ml kg−1 min−1), and running economy (51.1 ml kg−1 min−1 
at 268 m/min) and lactate threshold (~83% VO2max) values were comparable to 
that of highly trained distance runners. Two hours post-race, considerable changes 
in the ultrarunners’ gut microbiome were observed. Alpha diversity (Shannon 
Diversity Index) increased from 2.73 to 2.80 and phylum-level bacterial composition 
(Firmicutes/Bacteroidetes ratio) rose from 4.4 to 14.2. Underlying these macro-level 
microbial alterations were demonstrable increases in select bacterial genera such as 
Veillonella (+14,229%) and Streptococcus (+438%) concomitant with reductions in 
Alloprevotella (−79%) and Subdolingranulum (−50%). To our knowledge, this case 
study shows the most rapid and pronounced shifts in human gut microbiome compo-
sition after acute exercise in the human literature. These findings provide yet another 
example of how exercise can be a powerful modulator of human health.
K E Y W O R D S
endurance exercise, gut microbiota, ultramarathon, Veillonella
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GROSICKI et al.
Recently, our group (Durk et al., 2018) and others (Allen 
et al., 2018; Keohane et al., 2019; Scheiman et al., 2019) have 
shown a link between physical activity and human microbi-
ome composition, aiding in the delineation of a signature mi-
crobiome response to exercise training. Increases in bacterial 
diversity and a proliferation of taxa responsible for the pro-
duction of short chain fatty acids, such as butyrate, are among 
the most pervasively observed microbial alterations with exer-
cise (Mailing, Allen, Buford, Fields, & Woods, 2019). While 
these changes are generally regarded as beneficial to the host, 
a comprehensive understanding of exercise training-induced 
microbial modifications and their systemic physiological 
implications remains to be delineated. Moreover, even less 
is known regarding the human gut microbiome response to 
an acute exercise bout. Recently, we had the unique oppor-
tunity to track the gut microbiome of a world-class ultra-
marathon runner who finished in the top-10 at the Western 
States Endurance Run, a 163 km mountain footrace featuring 
~5,486 m climbing and ~7,010 m of descent. Substantially re-
duced splanchnic blood flow over the course of the ~16-hr 
event in concert with tremendous energetic demands (13,000–
16,000 kcal) (Cuddy, Slivka, Hailes, & Dumke, 2009) pro-
vides a unique lens through which to study the plasticity of our 
microbial inhabitants under extreme conditions.
2 | 
METHODS
2.1 | Participant
The participant was a 32 yr old male world-class ultramara-
thon runner, studied over the course of a 21-week period dur-
ing the 2019 race season. He began running competitively 
in high school, and in college he was a two-time NCAA 
Division II Cross-Country All-American. He since raced in 
the Olympic marathon trials and is a two-time champion at 
the Javelina Jundred.
2.2 | Approval and screening
This project was approved by the Institutional Review Board 
at Georgia Southern University. On the day of the first study 
visit, project objectives and risks and procedures were ver-
bally explained to the participant, after which the participant 
provided written informed consent to participate. A visual rep-
resentation of the study methodology is provided in Figure 1.
2.3 | Training quantification
Daily training logs recorded via a Suunto Ambit3 Peak GPS 
watch provided by the ultramarathoner were utilized to 
quantify weekly and cumulative training duration, mileage, 
and pace.
2.4 | Body composition and bone 
mineral content
Height and body mass were measured on a wall-mounted 
stadiometer and calibrated digital scale, respectively. Body 
composition was assessed at 21 and 5  weeks prior to the 
Western States Endurance Run (WSER) (Figure 1) using 
dual-energy X-ray absorptiometry (DEXA) (Lunar iDXA, 
GE Healthcare). The DEXA machine was outfitted with 
enCORE version 16 and the machine was calibrated im-
mediately prior to each scan per manufacturer instructions 
(laboratory coefficient of variation  <  0.07%). Scans were 
obtained after an overnight fast (>10 hr) and after voiding 
of the bladder using “standard thickness” mode based on the 
subject's size characteristics.
2.5 | Submaximal and maximal oxygen 
consumption (VO2max) exercise testing
Submaximal exercise testing was performed on a slat 
belt treadmill (4Front, Woodway) 30 min after ingesting a 
150 kcal (23 g carbohydrate, 6 g fat, 1 g protein) solid snack 
(GU Energy Labs). Testing was performed in a tempera-
ture-controlled environment (22°C, 63% relative humid-
ity and 766.1 mmHg) using a protocol from McMiken and 
Daniels (1976) to facilitate running economy comparisons to 
a well-characterized cohort of high-caliber distance runners 
(Conley & Krahenbuhl, 1980; Costill, Thomason, & Roberts, 
1973). Testing stages were 6 min in duration and expired gas 
was monitored throughout the test via indirect calorimetry 
(TrueOne2400, Parvo Medics) while heart rate was monitored 
via wireless telemetry (Polar H10, Polar USA). At the com-
pletion of each testing stage, blood lactate was evaluated via 
finger-stick (Lactate Scout+, EKF Diagnostics). Submaximal 
testing was performed at a 0% grade using incremental steps 
in velocity (80, 134, 215, 268, 295 and 311 m/min) and pro-
ceeded until blood lactate exceeded 4  mmol/l. Gas values 
(e.g., O2 consumption, respiratory exchange ratio, etc.) were 
quantified using the average of two 30 s values during the last 
minute of each testing stage and rating of perceived exertion 
(RPE, Borg scale) (Borg, 1970) was assessed in the last 15 s 
of each stage.
Based on a recent report of performance testing in a 
world-class cyclist (Bell, Furber, Someren, Anton-Solanas, 
& Swart, 2017), a 15 min rest period was provided between 
submaximal and maximal (VO2max) treadmill exercise test-
ing. The VO2max test was administered in 2-min stages at 0% 
grade, beginning at 80 m/min and working up to the velocity 
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GROSICKI et al.
at lactate threshold (295 m/min). After 2 min at this velocity, 
the grade was increased to 4% and then another 2% for every 
2 min thereafter until volitional exhaustion. Oxygen consump-
tion, heart rate and RPE were monitored using the same equip-
ment and testing procedures as described above. Attainment 
of VO2max was verified by (a) achievement of greater than 
or equal to 90% age-predicted maximal heart rate, (b) a respi-
ratory exchange ratio (RER)> 1.1, and (c) a final RPE > 17.
2.6 | Gut microbiome analyses
Gut microbiome analyses were performed at four time-points 
(21 and 2 weeks pre-WSER, 2 hours and 10 days post-WSER), 
as shown in Figure 1. Stool samples were self-collected by the 
ultramarathoner using a commercially available kit (Ubiome 
Explorer) in accordance with the specifications laid out by 
the NIH Human Microbiome Project (McInnes, 2010). All 
samples, besides the 2  hr post sample, were taken at ap-
proximately the same time of day before eating or exercis-
ing (0800). Following a bowel movement, a sterile swab was 
used to transfer a small amount of fecal matter into a vial con-
taining a lysis and stabilization buffer that preserves the ge-
netic material for transport at ambient temperatures. Samples 
were sent to Ubiome laboratories (Ubiome) (Bik et al., 2018) 
and lysed by bead-beating prior to DNA extraction in a class 
1,000 clean room using a guanidine thiocyanate silica col-
umn-based purification method via a liquid-handling robot. 
PCR amplification of the 16S rRNA genes was performed 
with primers containing universal primers amplifying the V4 
variables region (515F: GTGCCAGCMGCCGCGGTAA and 
806R: GGACTACHVGGGTWTCTAAT) (Caporaso et al., 
2011). In addition, the primers contained Illumina tags and 
barcodes. Samples were barcoded with a unique combination 
of forward and reverse indexes allowing for simultaneous 
processing of multiple samples. PCR products were pooled, 
column-purified, and size selected through microfluidic DNA 
fractionation (Minalla & Dubrow, 2001). Consolidated librar-
ies were quantified using quantitative real-time PCR using the 
Kapa iCycler qPCR kit (Bio-Rad) on a BioRad Myio before 
loading into the sequencer. Sequencing was performed in a 
pair-end modality on a NextSeq 500 platform (Illumina) ren-
dering 2 × 150 bp pair-end sequences. These DNA sequencing 
techniques were then used to generate data outputs (.csv file) 
that provided a comprehensive bacterial taxonomic profile. 
Shannon diversity index (i.e., alpha diversity) was computed 
using PAST: Paleontological statistics software package  
for education and data analysis (version 3.25) (Hammer  
et al., 2001).
3 | 
RESULTS
3.1 | Training quantification
For the 6 weeks prior to the WSER-specific training block, 
the athlete was running ~115  km per week over mostly 
flat ground with little strength training. Over the course 
FIGURE 1 
Visual representation 
of study design. Anthropometric and 
physiological measurements including 
cardiorespiratory fitness (treadmill) were 
first taken 21 weeks prior to Western States 
Endurance Run (WSER; 163 km mountain 
footrace from Squaw Valley, CA to Auburn, 
CA) and are reported in the text as Baseline 
results. Body composition (scale) and gut 
microbiome composition (fecal symbol) 
were intermittently evaluated throughout the 
observational period. Relevant events prior 
to the race such as a training camp (tent) and 
shorter/preparatory races (race flags) have 
been highlighted for temporal interpretation
4 of 7 | 
  
GROSICKI et al.
of the 21-week training block, the participant increased 
volume slightly (~124 km at an average pace of 201 m/
min) and supplemented with an additional 120 min per 
week of strength and stretching exercises, accumulating 
15,331 total minutes of training time. The largest vol-
ume of training consisted of an eight-day training camp in 
northern California 4–5 weeks prior to WSER (Figure 1), 
during which the ultramarathon runner accumulated 1,037 
total minutes of training time (987 min running) and cov-
ered 177 km with 6,016 m elevation gain. To prepare for 
WSER, the athlete competed in a 50 k trail race at week 4, 
much of which was on the WSER trail, as well as a 100 k 
sponsor-endorsed road race. During the 10-day post-race 
observation period, the athlete refrained from any struc-
tured exercise for seven days before beginning light jog-
ging (~5:30/km) for 30–60 min duration.
3.2 | Body composition and bone 
mineral content
Baseline body mass and height were 64.0 kg and 170 cm, 
respectively, and body fat mass was 14.8%. Regional dis-
tribution of baseline body fat mass was 17.2%, 12.8% and 
13.7% for the arms, legs and trunk, respectively. Bone min-
eral content was 2.6 kg and total body bone mineral den-
sity was 1.074  g/cm2 (NHANES/Lunar T-score  =  −1.3) 
(WHO Study Group, 1994). After 15  weeks of WSER-
specific training, body mass increased slightly (+0.5 kg) 
and total body fat was reduced to 14.2% due to compo-
sitional shifts in the arms and legs (16.5% and 12.7%, re-
spectively). Although bone mineral content was identical 
between visits, bone mineral density improved to 1.086 g/
cm2 (T-score = −1.1), with the most notable changes oc-
curring in the spine and pelvis (Table 1).
3.3 | Submaximal and maximal oxygen 
consumption (VO2max) exercise testing
Submaximal testing lasted 24 min, concluding after comple-
tion of a 6-min stage at 311 m/min (~5:10 min/mile) where 
blood lactate reached 6.1 mmol/l and relative oxygen con-
sumption (VO2) was 61.8  ml  kg−1  min−1. At velocities of 
268 and 295 m/min, VO2 was 51.1 and 55.3 ml kg−1 min−1, 
running economy values comparable or even superior to 
those reported by Costill, Thomason and Roberts (51.7 and 
59.0  ml  kg−1  min−1 at corresponding velocities) in highly 
trained distance runners (Costill et al., 1973).
Maximal exercise testing was terminated upon voli-
tional exhaustion (RPE = 20) at 295 m/min at an 8% grade. 
Maximal oxygen consumption (VO2max) was 4.24  L/min 
(66.7 ml kg−1 min−1) and maximal heart rate and RER values 
were 186 bpm and 1.19, respectively. Maximal ventilation was 
130.7 L/min. Based on these maximal values, lactate threshold 
was estimated to occur at ~83% VO2max (RER = 0.89).
3.4 | Gut microbiome analyses
Microbial diversity (Shannon Diversity Index) oscillated 
throughout the investigation, decreasing following 19-week 
of highly specific race preparation but then increasing post-
event (Figure 2a). Firmicutes/Bacteroidetes ratio, a macro-
level indicator of microbial composition, was relatively stable 
pre-WSER (~5:1), but nearly tripled 2 hr post-race due to a 
69% reduction in Bacteroidetes relative abundance (Figure 
2b). Meanwhile, the relative proportion of Proteobacteria in-
creased by more than fivefold 2 hr post-race, largely owing 
to a 29-fold increase in Haemophilus (Figure 2c). Other no-
table changes in gut microbiome composition post-WSER 
included the proliferation of Veillonella (+14,229%) and 
Streptococcus (+438%) genera concomitant with reductions 
in Alloprevotella (−79%) and Subdolingranulum (−50%).
4 | 
DISCUSSION
Manipulating the human microbial ecosystem has pro-
lific health implications and emerging therapeutic poten-
tial (Khanna & Tosh, 2014). To our knowledge, this case 
study shows the most rapid and pronounced gut microbiome 
changes after acute exercise in the human literature. These 
extraordinary microbial dynamics highlight the importance 
of physical activity in determining human microbiome as-
sembly and emphasize yet another way in which human 
movement can be one of the most powerful modulators of 
human health.
Taxonomic richness (i.e., alpha diversity) is often con-
sidered a key indicator of gut microbiome health that is gen-
erally thought to increase with exercise training (Estaki et 
TABLE 1 
Regional bone mineral density (g/cm2) in a world-
class ultramarathon runner preparing for the Western States 100-mile 
Endurance Race
 
Baseline
Pre-race
%Δ
Head
1.931
1.910
−1.088
Arms
0.647
0.653
+0.927
Legs
1.264
1.273
+0.712
Trunk
0.890
0.907
+1.910
Ribs
0.739
0.742
+0.406
Spine
0.970
0.992
+2.268
Pelvis
0.984
1.014
+3.048
Total
1.074
1.086
+1.117
   | 
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GROSICKI et al.
al., 2016), as was recently observed throughout an ultra-en-
durance rowing race (Keohane et al., 2019). Paradoxically, 
in this study alpha diversity, depicted as Shannon Diversity 
Index, decreased following 19  weeks of highly specific 
race preparation (2.83–2.73). This observation may be 
attributed to the proliferation of select advantageous bac-
terial taxa, such as those involved in butyrate production 
(e.g., Faecalibacterium, +40% baseline to pre-race), con-
comitant with the decline of less relevant microorganisms. 
In contrast, unpublished observations from our laboratory 
in a cohort of 28 young recreationally active individuals 
(~30 years) demonstrated alpha diversity changes of plus or 
minus 0.05 over a 3-week time period. Post-race, alpha di-
versity increased by a similar extent (+0.07) nearly reaching 
baseline levels (2.80). Of the post-race changes in relative 
genus abundance, a likely beneficial 143-fold increase in 
Veillonella (~10% relative abundance post-WSER) was the 
most pronounced. Indeed, Scheiman et al. (2019) recently 
proposed an ergogenic role for Veillonella involving lactate 
recycling after observing a similar, albeit less profound, el-
evation (~3% relative abundance) in Veillonella of runners 
1–5 days after the Boston Marathon.
While an increase in Veillonella abundance was likely 
a highly favorable adaptation to the 163  km race, other 
microbial dynamics such as post-race insurgences of 
Haemophilus, a bacterial genus composed of many sig-
nificant pathogenic species (e.g., H.  Influenzae) and 
Streptococcus (genus-level taxon of Group A Streptococcus 
pyogenes) were also observed. It may be speculated that 
intestinal proliferation of pathogenic bacterial species 
plays a role in the increased incidence of infectious epi-
sodes observed in endurance athletes following prolonged 
endurance exercise (Nieman, Johanssen, Lee, & Arabatzis, 
1990). Moreover, reductions in butyrate-producing bacteria 
FIGURE 2 
Tracking the microbiome of a world-class ultramarathon runner. (a) Alpha diversity, represented as Shannon Diversity Index 
(H), of the gut microbiome in a world-class ultramarathon runner measured at Baseline (21 week pre-Western States Endurance Run [WSER; 
163 km mountain footrace]), Pre-Race (2 week pre-WSER), Post-Race (2 hr post-WSER), and Recovery (10 days post-WSER) measured via 16S 
rRNA sequencing. (b) Relative phylum-level gut microbiome composition changes at the same time-points listed above. (c) Relative abundance 
of bacteria genera over the course of the investigation. Genera comprising ≥5% of total fractional abundance for at least one time-point are 
individually represented while genera of lower abundance were condensed (Other)
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Relative Phylum Abundance (%)
Actinobacteria
Bacteroidetes
Firmicutes
Fusobacteria
Proteobacteria
2.60
2.65
2.70
2.75
2.80
2.85
2.90
Baseline
Pre-Race
Post-Race
Recovery
α-Diversity (Shannon Diversity Index)
a
b
c
Pre-Race
Post-Race
100
90
80
70
60
50
40
30
20
10
0
Baseline
0
5
10
15
20
25
30
35
40
45
50
55
60
65
70
75
80
85
90
95
100
Relative Genus Abundance (%)
Alloprevotella
Anaerostipes
Blautia
Faecalibacterium
Haemophilus
Pseudobutyrivibrio
Roseburia
Streptococcus
Subdolingranulum
Veillonella
Other
Recovery
6 of 7 | 
  
GROSICKI et al.
(e.g., Subdolingranulum) associated with mucosal integrity 
likely exacerbate this state of hypervulnerability to infec-
tion as well as contributing to elevated levels of circulat-
ing inflammation (Gill et al., 2015; Grosicki, Fielding, & 
Lustgarten, 2018) and gastrointestinal distress (Jeukendrup 
et al., 2000). Surprisingly however, the athlete did not re-
port any significant gastrointestinal complaints during or 
following the event. Interpreted together, genus-level shifts 
in gut microbiome composition post-WSER highlight the 
complexity of interpreting microbiome data and reinforce 
the importance of avoiding oversimplifying macro-level 
observations (e.g., F/B ratio and/or alpha diversity) of mi-
crobial community structure (Shade, 2017).
In conclusion, these data add to a growing body of litera-
ture demonstrating the potency of acute exercise in shaping 
human microbiome composition. Though other factors (e.g., 
diet, travel, etc.) may have influenced our findings, no purpose-
ful changes in diet or feelings of malaise were reported by the 
ultramarathon runner over the course of the data collection pe-
riod. Nonetheless, more research involving carefully structured 
training studies in both healthy and clinical populations and 
interdisciplinary research teams is needed to fully understand 
the complex interaction between physical activity and the gut 
microbiome.
ACKNOWLEDGMENTS
We would like to thank the ultramarathon runner for his en-
thusiastic participation as well as his coaches, Roxanne Vogel 
and Magdalena Boulet, for their contributions to his success. 
We would also like to thank Amanda Fernandez, B.S. (Georgia 
Southern University), Brett Cross, B.S. (Georgia Southern 
University), and Gwenaelle Begue, Ph.D. (Sacramento State 
University) for technical assistance, and Michael Lustgarten, 
Ph.D. (Tufts University) for analytical insight.
CONFLICT OF INTEREST
The authors have no conflict to disclose.
AUTHOR CONTRIBUTIONS
GJG and JRB conceived and designed the research. GJG, 
RPD, and RJB performed the experiments, analyzed data, 
interpreted results of experiments, and prepared the figures. 
GJG drafted the manuscript. GJG, RPD, and JRB edited, re-
vised, and approved the final version of the manuscript.
ORCID
Gregory J. Grosicki 
 https://orcid.org/0000-0001-8929-4903 
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How to cite this article: Grosicki GJ, Durk RP, 
Bagley JR. Rapid gut microbiome changes in a 
world-class ultramarathon runner. Physiol Rep. 
2019;7:e14313. https ://doi.org/10.14814/ phy2.14313 

Rapid gut microbiome changes in a world-class ultramarathon runner.
Grosicki, Gregory J,Durk, Ryan P,Bagley, James R