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Gut microbiota in human SLE and a mouse model of 1
lupus 2
3
4
Xin M. Luo1# ([email protected]) 5
Michael R. Edwards1 ([email protected]) 6
Qinghui Mu1 ([email protected]) 7
Yang Yu2 ([email protected]) 8
Miranda D. Vieson1 ([email protected]) 9
Christopher M. Reilly3 ([email protected]) 10
S. Ansar Ahmed1 ([email protected]) 11
Adegbenga A. Bankole4# ([email protected]) 12
13
14 1Department of Biomedical Sciences and Pathobiology, Virginia-Maryland College of Veterinary 15
Medicine, Virginia Tech, Blacksburg, Virginia 16 2Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los 17
Angeles, California 18 3Edward Via College of Osteopathic Medicine, Blacksburg, Virginia 19
4Virginia Tech Carilion School of Medicine, Roanoke, Virginia 20
21
#Address correspondence to Xin M. Luo, [email protected]; and Adegbenga A. Bankole, 22
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25
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Running title: Lupus and Microbiota 27
28
AEM Accepted Manuscript Posted Online 1 December 2017Appl. Environ. Microbiol. doi:10.1128/AEM.02288-17Copyright © 2017 American Society for Microbiology. All Rights Reserved.
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Abstract 29
Gut microbiota dysbiosis has been observed in a number of autoimmune diseases. However, the role of 30
gut microbiota in systemic lupus erythematosus (SLE), a prototypical autoimmune disease characterized 31
by persistent inflammation in multiple organs of the body, remains elusive. Here we report the dynamics 32
of gut microbiota in a murine lupus model, NZB/W F1, as well as intestinal dysbiosis in a small group 33
of SLE patients with active disease. The composition of gut microbiota changed markedly before and 34
after the onset of lupus disease in NZB/W F1 mice, with higher diversity and increased representation of 35
several bacterial species as lupus progressed from pre-disease to the diseased stage. However, we did 36
not control for age and the cage effect. Using dexamethasone as an intervention to treat SLE-like signs, 37
we also found that a higher abundance of a group of Lactobacilli (to which a species assignment could 38
not be made) in the gut microbiota might be correlated with more severe disease in NZB/W F1 mice. 39
Results of the human study suggest that, compared to controls without immune-mediated diseases, SLE 40
patients with active lupus disease possessed an altered gut microbiota that was different in several 41
particular bacterial species (within the genera Odoribacter, Blautia and unnamed genus under the family 42
Rikenellaceae), less diverse, and with increased representation of Gram-negative bacteria. The ratio of 43
Firmicutes to Bacteroidetes was not different between SLE microbiota and Non-SLE controls in our 44
human cohort. 45
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Importance 46
Systemic lupus erythematosus (SLE) is a complex autoimmune disease with no known cure. Dysbiosis 47
of gut microbiota has been reported in both mouse and human with SLE. However, as an emerging field 48
more studies are required to delineate the roles of gut microbiota in different lupus-prone mouse models 49
and people with diverse manifestations of SLE. Here, we report changes of gut microbiota in NZB/W F1 50
lupus-prone mice and a group of SLE patients with active disease. 51
52
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Introduction 53
Systemic lupus erythematosus (SLE) is a prototypical autoimmune disease that affects almost all organs 54
of the body. It exhibits diverse manifestations that are a challenge to clinicians. The etiology of SLE is 55
unclear, but evidence has shown that it is influenced by genetic, environmental, hormonal, and 56
epigenetic factors (1). Together these factors act on the immune system and cause abnormalities 57
including the generation of autoantibody-producing B cells and autoreactive T cells, as well as abnormal 58
production of proinflammatory cytokines. The hallmark of the disease is characterized by severe 59
inflammation at target organs that leads to tissue damage. The products of damaged cells are picked up 60
by autoantibodies to create immune complexes that activate antigen-presenting cells, which in turn 61
induce more inflammatory T cells and proinflammatory cytokines, creating a vicious cycle of 62
inflammation (2). Current standard of care treatments for SLE are mainly nonselective 63
immunosuppressants (3). Not all patients respond to these treatments, and systemic immunosuppression 64
is a major cause of concern. Higher incidence of and more severe infections have been observed in 65
patients taking long-term non-selective immunosuppressants (4). There is an imperative need to better 66
understand the pathogenesis of SLE, from which new treatment strategies may be developed. 67
Environmental factors, including diet, modern medicine and environmental microbes, are 68
involved in the etiology of SLE. This is supported by observations in both human and mouse. The 69
incidence of SLE is significantly higher in African Americans than West Africans, although the two 70
populations are genetically very similar (5). In lupus-prone mice, the involvement of environmental 71
factors is evidenced by the progressive loss of SLE-like phenotype observed in the classical lupus-prone 72
strain MRL/Mp-Faslpr
(MRL/lpr) over several years at The Jackson Laboratory under specific pathogen-73
free conditions, while no deviation from the original strain was detected at the genetic or epigenetic 74
level (Stock Number 006825). As diet, medicine and environmental microbes can influence the 75
composition of host microbiota, efforts have been made to understand the dynamics of microbiota—76
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largely commensal bacteria living in our gut—in the pathogenesis of SLE. Oral antibiotics are known to 77
trigger lupus flares (6-8), suggesting a role for commensal bacteria in SLE. Our research team has 78
recently described changes of gut microbiota in lupus-prone mice vs. healthy controls (9), where a 79
decrease of Lactobacillaceae and an increase of Lachnospiraceae were observed in the MRL/lpr mouse 80
model (Jackson Laboratory Stock Number 000485). Interestingly, a treatment that improved lupus-like 81
symptoms also restored lactobacilli (9). Based on these observations, we administered Lactobacillus 82
spp. to MRL/lpr mice and showed a striking effect of the probiotics in ameliorating lupus nephritis (10). 83
This suggests that lupus disease could be controlled by changes of the gut microbiota. In another lupus-84
prone mouse model SNF1, a higher abundance of the Rikenellaceae family of commensal bacteria was 85
found to be associated with more severe SLE-like disease (11). Moreover, increased bacterial diversity 86
was observed in both MRL/lpr and SNF1 mouse models (9, 11). In human SLE, a cross-sectional study 87
showed that the fecal microbiota of SLE patients with inactive disease had a significantly lower 88
Firmicutes to Bacteroidetes ratio than that of healthy controls (12). A lower Firmicutes to 89
Bacteroidetes ratio is also evident in other autoimmune diseases (13, 14). The fecal microbiota of SLE 90
patients was also a stronger inducer of T helper-17 (Th17) differentiation than healthy control fecal 91
microbiota (15), whereas the Th17 response is considered a primary driver of autoimmunity in SLE (16-92
20). 93
Here, we report the dynamics of gut microbiota in another murine lupus model, NZB/W F1, as 94
well as an altered gut microbiota in a small group of SLE patients. 95
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Materials and Methods 96
Mice. Female NZB/W F1 mice were purchased from The Jackson Laboratory (Bar Harbor, ME) and 97
maintained in a specific pathogen-free facility according to the requirements of Institutional Animal 98
Care and Use Committee (IACUC) at Virginia Tech. For the time course, fecal pellets were collected 99
from untreated mice at 10, 14, 18, 23, 28, and 33 weeks of age, respectively. For the 10-, 14-, 18-week 100
time points, the same cage of mice (n=5) were sampled according to age. For the 23-, 28-, 33-week time 101
points, three different cages of mice (each representing a time point, n=3-4 for cage) were sampled. For 102
the experiment involving dexamethasone (Dex), age-matched mice treated with either Dex or vehicle 103
control were euthanized at 34 weeks of age. Hydroxy-propyl-methyl cellulose (HPMC, Sigma, St. 104
Louis, MO) was diluted in sterile deionized water at a concentration of 0.05%, autoclaved, then used as 105
the vehicle for the drug solutions. Ten mice (n=5 per cage per group) were included in each of the two 106
groups: vehicle control (HPMC) or 2 mg/kg Dex. Intraperitoneal injections were performed 5 times per 107
week with a 50 l volume of their respective treatments beginning at 20 weeks of age, and treatments 108
continued until euthanasia. Proteinuria (measured with Chemstrips) and body weight were measured 109
biweekly before treatment, then weekly after treatment began. 110
111
Evaluation of SLE-like disease in mice. Renal function was assessed and calculated as previously 112
described (9). The serum level of anti-double stranded DNA autoantibodies was measured as previously 113
described (21). Systemic autoimmunity was calculated as follows: (serum level of anti-dsDNA + 500 114
spleen-to-body weight ratio) / 2, where the coefficient 500 equalized the averages of the two variables. 115
116
Human subjects. The patients were enrolled at the lupus clinic in a single center in Southwest Roanoke, 117
Virginia. All patients met the 2009 Systemic Lupus International Collaborating Clinic (SLICC) revised 118
American College of Rheumatology (ACR) diagnostic criteria for SLE. At the time of enrollment, the 119
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medication list was collected and an SLE disease activity index (SLEDAI) score was obtained. The 120
inclusion criteria were: age 18-75, fulfilling SLICC revised ACR criteria for SLE (2009), and on or 121
eligible for immunosuppressive therapy. The exclusion criteria were: age <18 or >75, not meeting 122
SLICC revised ACR criteria for SLE, disease not needing immunosuppressive therapy, pregnancy, 123
presence of other immune diseases such as inflammatory bowel disease, on or recent use of antibiotics, 124
and vulnerable patients including prisoners, non-English speakers and critically ill patients. 125
126
Microbiota sampling, 16S rRNA analysis, and metagenome prediction. Mouse fecal microbiota were 127
obtained by taking individual mice out of their cage and collecting a fecal pellet. Colonic microbiota 128
samples were collected within 20 min after euthanasia. To avoid cross-contamination, each microbiota 129
sample was collected by removing the colon and extruding the fecal material into a sterile 1.5 mL 130
Eppendorf tube using a new pair of sterile forceps. Human fecal samples were collected from patients at 131
Carilion Medical Center in Roanoke, VA, between 2015 and 2016. For stool samples, patients were 132
provided with a collection “pot” and requested to bring in a specimen collected the day before a routine 133
visit. All procedures were approved by the Institutional Review Board (IRB) of Virginia Tech Carilion 134
School of Medicine. All microbiota samples were stored at -80°C until being processed at the same 135
time. Sample homogenization, cell lysis, DNA extraction and PCR of the 16S-V4 region were 136
performed with the same methods described in a previous report (9). Purified amplicons were sequenced 137
bi-directionally (paired-end 150 bp) on an Illumina MiSeq at Argonne National Laboratory. Sequence 138
read merge, quality filtering, de-replication, chimera removal, and OTU clustering were performed with 139
the UPARSE pipeline implemented in the USEARCH program version 8.1/1831 (22). Bacterial 140
taxonomy was assigned by using the ‘UclustConsensusTaxonAssigner’ implemented in QIIME (23) 141
against the Greengene reference database (24, 25), and summarized at all taxonomic levels (26). Alpha- 142
and beta-diversity metrics were computed with QIIME. Alpha-diversity included Shannon diversity 143
index and observed OTUs, and beta-diversity included unweighted UniFrac distance metrics (27, 28). 144
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Sequencing data have been deposited (NCBI SRA SRP092445), and the OTU results for all experiments 145
can be found in the supplemental materials. 146
147
Statistics. Two-sample comparison was performed by Student’s t-test or nonparametric Mann-Whitney 148
rank-based test. For >2 groups, one-way ANOVA or the nonparametric Kruskal-Wallis test was 149
performed. Because the Kruskal-Wallis test assumes identical distributions in each group, we also 150
performed ‘oneway.test’ in R for comparing means without assuming equal variances. Correlation 151
analysis using Spearman rank-based methods was performed. PCoA was tested for significance by a 152
permutational multivariate method PERMANOVA (29). When studying age as fixed effect and mouse 153
subject as random effect, we used the linear mixed model implemented in the ‘nlme’ package in R. P 154
values were corrected for multiple comparisons by controlling false discovery rates (FDR). All statistical 155
computations were performed in R version 3.3.1. 156
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Results 157
Dynamics of gut microbiota in NZB/W F1 mice 158
Like MRL/lpr mice, the disease phenotype in NZB/W F1 mice resembles human SLE and is 159
characterized by high levels of antinuclear antibodies, hemolytic anemia, proteinuria, and progressive 160
immune complex glomerulonephritis. These mice have been used as a model for human SLE since the 161
early 1960s due to their genetic resemblance of the complex multifactorial disease. Similar to human 162
SLE that has a strong female bias, the disease is most pronounced in female NZB/W F1 mice. The 163
average lifespan for females is 8 months, with disease onset at approximately 5 months (20 weeks) of 164
age. Thus, the disease progression is much slower in NZB/W F1 mice than in MRL/lpr mice. 165
To determine the dynamics of gut microbiota during lupus progression in female NZB/W F1 166
mice, we analyzed fecal pellets collected at 3 pre-disease time points (10, 14, 18 weeks of age) and 3 167
post-disease onset, or diseased, time points (23, 28, 33 weeks of age). The structure and diversity of 168
lupus-associated microbiota changed continuously over time (Figure 1). The unweighted UniFrac 169
distance-based principal coordinate analysis (PCoA) showed that the gut microbiota was distinct at 3 170
different pre-disease time points, but clustered together at the diseased time points (Figure 1A and 171
Figure S1). Importantly, the UniFrac distance between pre-disease and diseased time points was greater 172
than the distance observed within the 3 pre-disease time points. In addition, the gut microbiota split into 173
two groups along the PC1 axis (P < 0.01, PERMANOVA), and the split happened at around 20 weeks of 174
age, suggesting a dramatic change of gut microbiota upon the onset of SLE-like symptoms. It is worth 175
noting that we cannot rule out the cage effects that may be driving the differences in Figure 1A, and that 176
we do not have a wildtype control for the effects of aging on the microbiota. 177
We next determined the change of microbiota diversity during lupus progression in NZB/W F1 178
mice. The number of operational taxonomic units (OTUs) in these mice increased significantly from 179
pre-disease to diseased stages (P < 0.001, Figure 1B), suggesting increased bacterial diversity as disease 180
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progressed. This is consistent with other lupus-prone mouse models where lupus-associated increase in 181
microbiota diversity was also observed (9, 11). Individual bacterial species fluctuated during the time 182
course tested, and the species with significant changes are shown in Figure 1C. Specifically, significant 183
increases from pre-disease to diseased stage were observed for several bacterial species under the genera 184
Clostridium, Dehalobacerium, Lactobacillus, Oscillospira, Dorea (family Lachnospiraceae), Bilophila 185
(family Desulfovibrionaceae), AF12 (family Rikenellaceae), and an unnamed genus within the family 186
Ruminococcaceae (P < 0.01 for all cases). Akkermansia muciniphila and a species within the genus 187
Anerostipes (family Lachnospiraceae), on the other hand, significantly decreased from pre-disease to 188
diseased stage (P < 0.01). These results suggest that the composition of gut microbiota changed 189
markedly before and after the onset of lupus disease in NZB/W F1 mice, with higher diversity and 190
increased representation of several bacterial species as lupus progressed from pre-disease to the diseased 191
stage. It is worth noting that these changes may also be caused by the maturation of bacterial 192
communities as the mice aged. 193
To determine whether a common treatment of SLE could reverse the changes in gut microbiota, 194
we treated NZB/W F1 mice with 2 mg/kg body weight dexamethasone (Dex) from 20 to 34 weeks of 195
age (14 weeks of treatment). Prior studies have shown that Dex suppresses the development of disease 196
in NZB/W F1 lupus-prone mice (30). Treatment with Dex altered the microbiota as the animals aged 197
compared to the vehicle-treated controls (Figure 2). The overall microbiota structure with Dex treatment 198
was distinct from the vehicle treatment (Control) as shown in the unweighted UniFrac-based PCoA plot 199
(Figure 2A, P < 0.01). Interestingly, instead of decreasing the bacterial diversity that was already high in 200
diseased mice (Figure 1B), Dex appeared to have further increased the diversity with a significantly 201
higher Shannon index and higher observed OTUs (Figure 2B and Figure S2, P < 0.001 for both cases). 202
Notably, the community variability decreased (Figure 2A) while diversity increased (Figure 2B) in Dex-203
treated mice compared to control mice. We interpret that high diversity in the Dex group may lead to a 204
more stable community, therefore the lower observed variability than the control group. 205
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We next identified the bacterial species with significant changes from pre-disease onset (pre) to 206
post-disease onset (post) and whether Dex treatment significantly reversed such changes. Only one 207
bacterial species, Lactobacillaceae_Lactobacillus_Other, fulfilled these criteria (Figure 2C). The 208
relative abundance of this species significantly increased from 0.01% at pre-disease stage to 10% post-209
disease onset, and Dex was able to significantly decrease it to 1% (P < 0.01 in both cases). BLAST 210
(Basic Local Alignment Search Tool) analysis showed that the OTU sequences within 211
Lactobacillaceae_Lactobacillus_Other were at least 98% identical to those of Lactobacillus murinus, 212
Lactobacillus kimchicus, and Lactobacillus senmaizukei. Among the three, only Lactobacillus murinus 213
was isolated from mice (the other two were from kimchi and Japanese pickle, respectively). However, 214
there could be unsequenced isolates that could be represented by the sequence obtained from the 16S 215
analysis; therefore, the isolate(s)’ identity is unknown but could be one or more of the three detected 216
species. We further studied Spearman association coefficients between this bacterial species and two 217
measurements of SLE disease state, renal function (abbreviated as RenalFunc in Figure 2D) and 218
systemic autoimmunity (abbreviated as SysAuto in Figure 2D). The renal function was calculated as a 219
composite score between the level of proteinuria and histopathological score, whereas systemic 220
autoimmunity was calculated as a composite score between the level of anti-double stranded DNA 221
autoantibodies and the weight of spleen (see Materials and Methods for details). Correlation analysis 222
showed that Lactobacillaceae_Lactobacillus_Other was positively associated with renal functions 223
(correlation efficient 0.38, P = 0.094) and systemic autoimmunity (correlation efficient 0.42, P = 0.067), 224
although the associations were not statistically significant. These results suggest that a higher abundance 225
of a group of Lactobacilli (to which a species assignment could not be made) in the gut microbiota may 226
be associated with more severe clinical signs in female NZB/W F1 mice. This is distinct from what has 227
been observed for female MRL/lpr mice, where a higher abundance of Lactobacillus reuteri was found 228
to be associated with disease attenuation (9, 10). 229
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Gut microbiota dysbiosis in human SLE patients 231
To study the differences in gut microbiota of patients with SLE compared to patients without immune-232
mediated diseases, we enrolled 14 patients with active SLE and 17 Non-SLE controls. Although the 233
overall community structure could not be separated by unweighted UniFrac-based PCoA analysis 234
(Figure 3A), SLE subjects had significantly lower diversity measured as Shannon index (Figure 3B, P < 235
0.05, Mann-Whitney test). Unlike the published comparison between healthy controls and SLE patients 236
where the ratio of Firmicutes/Bacteroidetes was significantly lower in SLE patients in remission (12), 237
the ratio was not significantly different between our cohort of SLE patients and Non-SLE controls 238
(Figure 3C, P > 0.05). In addition, the bacterial phylum Proteobacteria (a representation of facultative 239
anaerobic Gram-negative bacteria) was significantly higher in the gut microbiota of SLE patients 240
(Figure 3D, P < 0.05). This is consistent with the increased serum level of lipopolysaccharide (LPS) 241
endotoxin in SLE patients that was observed by others (31). Three bacterial species appeared to be 242
differentially represented in SLE subjects compared to Non-SLE controls (Figure 3E, P < 0.05 based on 243
both nonparametric Mann-Whitney test and DESeq2). They were each within the genera Odoribacter, 244
Blautia (family Lachnospiraceae) and an unnamed genus (family Rikenellaceae). BLAST analyses on 245
the OTU sequences were performed and the identified species are presented in Table 1. These results 246
suggest that compared to controls without immune-mediated diseases, SLE patients with active lupus 247
disease possessed an altered gut microbiota that was different in several bacterial species, less diverse, 248
and with increased representation of Gram-negative bacteria. Medication (Table 2) may influence the 249
composition and diversity of gut microbiota, but due to the small sample size, we did not attempt to 250
analyze the effects of medication. 251
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Discussion 252
In our studies, we analyzed the gut microbiota of NZB/W F1 mice and SLE patients with active disease 253
by using 16S rRNA sequencing. In NZB/W F1 mice, significant differences were observed in the gut 254
microbiota between pre-disease and diseased mice, and between untreated mice vs. mice treated with the 255
immunosuppressive drug Dex. The microbiota tends to be more diverse as disease progresses, and after 256
Dex treatment. In addition, a higher relative abundance of a group of Lactobacilli (to which a species 257
assignment could not be made) in the gut microbiota may be associated with deteriorated disease in 258
NZB/W F1 mice. Fewer differences were found in the comparison between Non-SLE individuals and 259
SLE patients with active disease. The fecal microbiota was less diverse in SLE patients, whereas the 260
Firmicutes/Bacteroidetes ratio was not different between the two groups. Interestingly, the relative 261
abundance of Proteobacteria representing LPS-containing Gram-negative bacteria was significantly 262
increased in SLE microbiota. 263
We found that human SLE patients have an altered microbiome in active disease when compared 264
to Non-SLE controls. The studies expand those of Hevia et al. (12) that reported SLE patients with 265
inactive lupus disease had a significantly lower Firmicutes/Bacteroidetes ratio than healthy control 266
individuals. However, we did not observe a similar change of the ratio in our cohort. This is possibly 267
due to differences in study designs: 1) there may be differences between the gut microbiotas of patients 268
with active and inactive disease; 2) we included both female and male SLE patients of different 269
ethnicities with various levels of lupus disease manifestations, whereas Hevia et al. included only female 270
Caucasians with SLEDAI scores of lower than 8; and 3) we had chosen to include SLE patients in need 271
of immunosuppressive therapies, whereas Hevia et al. excluded those who had taken steroid or 272
immunological treatments. Our inclusion/exclusion criteria selected subjects that may better represent 273
the SLE patient population, because SLE disproportionately affects African Americans, and it does 274
occur in men in addition to women. 275
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The use of nonselective immunosuppressive therapies in lupus patients, such as Dex and 276
azathioprine, may have broad consequences on the gut microbiota. A study by Huang et al. showed that 277
Dex treatment can alter the gut microbiota in healthy C57BL/6 wild type mice by increasing the 278
prevalence of Firmicutes, Actinobacteria and Bifidobacterium, and that in an inflammatory bowel 279
disease model, the microbiota from Dex-treated donor mice can reduce colonic inflammation by reduced 280
IL-12p40 and IL-17 production compared to control donor mice (32). This evidence suggests that even 281
as immunosuppressive medications are directly acting to suppress inflammation from the patient’s cell, 282
these medications may also contribute to the formation of a microbiome that promotes the regulation of 283
inflammation locally in the gastrointestinal tract, and potentially at distant sites in the body. All human 284
fecal samples were from patients taking immunosuppressive medications. The characterization of the 285
gut microbiota from SLE patients who have not yet started therapy, compared to their respective 286
microbiota following treatment, would allow for a better understanding of how these broad-acting 287
medications are able to modulate microbial dysbiosis and affect the resultant autoimmune disease 288
phenotype. 289
In our previous studies we had compared the fecal microbiota of MRL/lpr mice to that of MRL 290
control mice (9). In this study, however, we did not compare the fecal microbiota of NZB/W F1 mice to 291
that of a control mouse strain. People have used NZB or NZW mice as controls for NZB/W F1 mice, but 292
both of these strains can develop anti-DNA autoantibodies and glomerulonephritis (according to 293
descriptions on the Jackson Laboratory website) like NZB/W F1. C57BL/6 mice is another possible 294
control strain. Without a control mouse strain, our results on the changes of microbiota over time (Figure 295
1) could be interpreted as either disease-related or age-related. Either way, our results are informative 296
because they provide new information on the longitudinal changes of gut microbiota in one additional 297
lupus-prone mouse strain. In addition, we tried to control for the cage effect (Figure S1). For the 10-, 14-298
, 18-week time points, we sampled the same cage of animals depending on the age, but the microbiota 299
was distinct. For the 23-, 28-, 33-week time points, while their microbiota clustered together, these 300
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samples were collected from 3 different cages, with each cage representing a time point. While our 301
intention had been to control for the cage effect, this design was not adequate. In particular, our results 302
may have been confounded by the time of sample collection. A better study design should involve both 303
the same cage of animals sampled at different times, and different ages of animals sampled at the same 304
time. It would be also interesting to co-house mice of different ages and determine whether the 305
microbiotas are still distinct. 306
We attempted to identify consensus in the changes of gut microbiota between mice (NZB/W F1, 307
MRL/lpr and SNF1) and our cohort of SLE patients. While it is consistent among different lupus-prone 308
mouse models that the gut microbiotas were more diverse as disease progressed, the microbial diversity 309
was significantly lower in SLE patients with active disease compared to Non-SLE controls. The only 310
consensus between mouse and human was the relative abundance of Lachnospiraceae that was 311
significantly higher in both MRL/lpr mice (9) and SLE patients. However, in humans the increase was 312
limited to a species in the genus Blautia; when looking at the entire Lachnospiraceae family, the 313
difference was no longer evident. In future investigations, we will try to enroll a larger population of 314
SLE patients, divide them based on different disease manifestations, and analyze the gut microbiota 315
separately. This way consensus may be achieved between mouse and human enabling us to continue 316
using mice to model the human disease with regard to the roles of microbiome in lupus. 317
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Acknowledgements 318
We thank Sarah Henderson for coordinating the collection of patient samples, Sarah Owens and 319
Saikumar Karyala for assistance on Illumina MiSeq sequencing, Husen Zhang for microbiome analysis, 320
and Yingxing Wu for assisting in statistical analysis. 321
322
Conflict of Interest Statement 323
The authors declare no conflict of interest (such as defined by ASM policy). 324
325
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Figure Legends 408
Figure 1. Dynamics of gut microbiota in NZB/W F1 mice. Fecal pellets were collected at 10, 14, 18 409
weeks of age (pre-disease time points, n=5 per time point) and 23, 28, 33 weeks of age (post-disease 410
onset time points, n=3 or 4 per time point) and subjected to 16S rRNA sequencing analysis. The disease 411
onset in NZB/W F1 mice is around 20 weeks of age. (A) PCoA plot showing alteration of overall 412
community structures (P < 0.01). (B) Bacterial diversity indicated by the number of OTUs. The increase 413
of OTUs from pre-disease to post-disease onset stages was significant (P < 0.01). (C) Time-dependent 414
changes of the relative abundance of different bacterial species. Smoothing was done by ggplot2 415
package using locally weighted regression. P values were corrected for multiple comparisons by 416
controlling FDR (same in other figures). 417
418
Figure 2. Changes of gut microbiota in NZB/W F1 mice in response to immunosuppressant (Dex) 419
treatment. NZB/W F1 mice were treated with 2 mg/kg body weight Dex, intraperitoneal injection 5 per 420
week, from 20 to 34 weeks of age. Fecal pellets were collected at 34 weeks of age and subjected to 16S 421
rRNA sequencing analysis. (A) PCoA plot showing the separation of overall bacterial structure (P < 422
0.01). (B) Bacterial diversity indicated by the Shannon index (P < 0.001). (C) A bacterial species where 423
there was a significant change from pre-disease stage (pre) to post-disease onset stage (post), AND that 424
treatment of Dex significantly reversed the change (P < 0.01 in both cases). (D) Spearman correlation 425
analysis between the bacterial species identified in (C) and two measurements of SLE disease state – 426
renal function (RenalFunc) and systemic autoimmunity (SysAuto). See Materials and Methods for the 427
calculation of these two measurements. 428
429
Figure 3. Gut microbiota dysbiosis in SLE patients with active disease compared to Non-SLE controls. 430
The inclusion/exclusion criteria are shown in Materials and Methods. A fecal sample was collected from 431
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each patient or control at the time of the first visit, and the samples were subjected to 16S rRNA 432
sequencing analysis. (A) PCoA plot showing no separation of overall bacterial structure (P > 0.05). (B) 433
Significant difference in bacterial diversity indicated by the Shannon index (P < 0.05). (C) No 434
significant difference in the ratio of Firmicutes/Bacteroidetes (P > 0.05). (D) Significant difference in 435
the relative abundance of the phylum Proteobacteria, a representation of facultative anaerobic Gram-436
negative bacteria (P < 0.05). (E) Significant changes of several bacterial species with P values indicated 437
(nonparametric Mann-Whitney test). DESeq2 was also performed and the DESeq2 P values were 0.037, 438
0.007 and 0.007, respectively. P values were corrected for multiple comparisons by controlling FDR. 439
440
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Tables 441
Table 1. Differentially represented bacterial species between SLE and Non-SLE individuals. 442
Bacterial species Strain name OTU Sequence identity SLE compared to Non-SLE
Blautia wexlerae AUH-JLD17 7 100% Increased
Blautia wexlerae AUH-JLD56 7 100% Increased
Blautia sp. Marseille P3602 7 100% Increased
Blautia sp. GD8 / 23 100% Increased
Blautia faecis M25 25 100% Increased
Blautia caecimuris SJ18 492 99% Increased
Blautia sp. AUH-JLD3 / 585 98% Increased
Blautia sp. Marseille P3387 585 98% Increased
Odoribacter laneus JCM 63 100% Decreased
Odoribacter laneus YIT 63 100% Decreased
Odoribacter laneus JCM 63 100% Decreased
Odoribacter splanchnicus / 67 100% Decreased
Alistipes onderdonkii / 13 100% Decreased
Alistipes sp. LS-J 13 100% Decreased
Alistipes sp. LS-M 13 100% Decreased
Alistipes shahii WAL 8301 164 100% Decreased
Alistipes obesi ph8 164 100% Decreased
Alistipes ihumii AP11 188 100% Decreased
Alistipes sp. cv1 / 188/210 100% Decreased
Alistipes indistinctus JCM 188/252 100% Decreased
Alistipes indistinctus YIT 188/252 100% Decreased
Alistipes sp. S216 / 252 100% Decreased
Alistipes finegoldii DSM 17242 398 99% Decreased
Alistipes finegoldii JCM 16770 398 99% Decreased
Alistipes finegoldii CIP 107999 398 99% Decreased
Alistipes finegoldii AHN 2437 398 99% Decreased
443
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Table 2. Demographic, immunological, and clinical features of SLE patients. 444
Subject
No.
Age
(yrs)
Sex Race Immunological and clinical
features
SLEDAI
Score
BMI Medication
01
39 F AA ANA/dsDNA/C3/C4/heam
CL/PS
0 36.6 HCQ/Belimumab
02 21 F Caucasian
ANA/dsDNA/sm/C3/C4/heam
LN/PS/Alopecia/Neuro
8 36.4 HCQ/MMF/
Belimumab
03 40 F Caucasian
ANA/C3/C4/heam
Alopecia/SE
3 21.5 HCQ/MMF/
Belimumab
04 64 F AA ANA/C3/C4
Alopecia/MR/PS
6
31.4 HCQ/MMF/
Belimumab
05 65 F Caucasian ANA/dsDNA/C3/C4
LN
13 26.2 HCQ/MMF
06 41 M Caucasian ANA/dsDNA/C3
IA/PS/LN
2 43.5 MTX
07 27 M AA ANA/dsDNA/sm/ACL/C3/C4
LN/MR
6 31.6 HCQ/MMF
09 56 F Caucasian ANA/dsDNA/heam
PS
1 36.5 HCQ/MMF/
Belimumab
10 25 F Caucasian ANA/dsDNA/ACL/B2G/C3/C4
LN/MR/PS
8 39.1 HCQ/MMF/Rituxan
11 73 F Caucasian ANA/sm
SE
0 18.4 HCQ/MMF
17 23 M Caucasian ANA/dsDNA/heam
LN
2 21.0 PLQ/AZA
19 36 M Caucasian ANA/dsDNA/sm/C4/heam
MR/SE
0 37.2 HCQ/MMF
20 29 F AA ANA/dsDNA/sm/C3/C4
MR/IA
2 33.9 HCQ
23 66 F Caucasian ANA/dsDNA/heam
None
0 33.2 HCQ/AZA/Tacro
445
AA, African American (not Caribbean); Caucasian, Non-Hispanic; BMI, body mass index. 446
Immunological features: antinuclear antibody (ANA), anti-Smith antibody (sm), anti-dsDNA antibody 447
(dsDNA), Anti-cardiolipin antibody (ACL), 2 glycoprotein (B2G), lupus anticoagulant (LAC), 448
hematologic manifestation (heam), Complement C3 (C3), Complement C4 (C4). 449
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Clinical symptoms: inflammatory arthritis (IA), malar trash (MR), serositis (SE), lupus nephritis (LN), 450
cutaneous lupus (CL), photo-sensitivity (PS), neuro-lupus (Neuro). 451
Medications: Hydroxycholoquine (HCQ), Tacrolimus (Tacro), Mycophenolate mofetil (MMF), 452
Methotrexate (MTX), Azathioprine (AZA), Plaquenil (PLQ). 453
454
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