Colonization of breastfed infants by Bifidobacterium longum subsp. infantis EVC001 reduces virulence gene abundance

Accepted Manuscript Colonization of breastfed infants by Bifidobacterium longum subsp. infantis EVC001 reduces virulence gene abundance. Giorgio Casaburi, Steven A. Frese PII: DOI: Reference:

S2452-2317(18)30013-7 https://doi.org/10.1016/j.humic.2018.05.001 HUMIC 36

To appear in:

Human Microbiome Journal

Received Date: Revised Date: Accepted Date:

10 April 2018 2 May 2018 18 May 2018

Please cite this article as: G. Casaburi, S.A. Frese, Colonization of breastfed infants by Bifidobacterium longum subsp. infantis EVC001 reduces virulence gene abundance., Human Microbiome Journal (2018), doi: https://doi.org/ 10.1016/j.humic.2018.05.001

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Colonization of breastfed infants by Bifidobacterium longum subsp. infantis EVC001 reduces virulence gene abundance. Giorgio Casaburia, Steven A. Fresea,b,* a b

Evolve BioSystems, Inc., Davis, California 95618 USA Department of Food Science and Technology, University of Nebraska, Lincoln, Nebraska 68583 USA

*Corresponding author at Evolve BioSystems, Inc., Davis, CA 95618, USA E-mail address: [email protected] (S. Frese). ABSTRACT The infant gut microbiome is rapidly colonized by bacteria from the environment after birth, and this gut ecosystem can facilitate expansion of potential pathogens. Human milk shapes the infant gut microbiome and has evolved to foster the growth of specific bacteria. Breastfed infants also fed the coevolved infant gut symbiont Bifidobacterium longum subsp. infantis EVC001 had significant modifications to their gut metagenome, including a decreased number of virulence factor genes.

Keywords Bifidobacterium longum subsp. infantis EVC001 Gut microbiome Human milk Infants Virulence factors

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Virulence factors (VFs) enable bacterial survival and infection in the host1 and exhibit a broad spectrum of functions that are indispensable for microbes to achieve colonization, evade the host immune system and obtain nutrients from the host2, 3. The advancement of molecular techniques, particularly metagenomics, has allowed extensive characterization of the VF mechanisms, thus enabling a deeper understanding of bacterial pathogenesis2. Neonates are particularly susceptible to microbial infections since the infant gut has low microbiome stability and colonization resistance4. In this environment, microbes with VFs can easily establish persistent reservoirs and colonize newborn infants5. A rising global incidence of bacteria resistant to several classes of antibiotics and a progressive decrease in their effectiveness limit effective therapies,6,7and infections are a leading cause of death in infant intensive care units8. Recent studies have shown how commensal bacteria play a key role in the evolution and dissemination of VFs, even if they do not directly express virulence genes9, 10. There are limited ways by which VFs and the organisms that harbor them can be restricted without the use of antibiotics. In a recent clinical trial, we demonstrated how a single-strain probiotic containing Bifidobacterium longum subsp. infantis EVC001 fed to breastfed infants changed the gut microbiome composition to improve its stability and function11. In the present study, we extended our findings from our previous clinical trial11 using shotgun metagenomic sequencing to examine whether colonization by B infantis EVC001 significantly reduces the abundance of potential pathogens, and their VFs, in the healthy breastfed-infant gut microbiome. Shotgun metagenome sequencing was performed on 60 fecal samples collected at day 21 postnatal. The mothers of 29 breastfed infants were provided lactation support, and the infants were fed B. infantis EVC001 daily (EVC001-fed) from day 7 postnatal. Another 31 mothers received only lactation support and their infants were not fed B. infantis EVC001 (controls). B. infantis is a well-characterized organism for which there is extensive evidence of evolutionary adaptation to the breastfed infant gut12,13. However, the infant gut microbiome in resource-rich countries has experienced a progressive loss of B. infantis, likely due to high rates of Cesarean section delivery, formula feeding and antibiotics usage over the last three generations14. Metagenomic analysis using clade-specific marker genes to unambiguously assign reads to functional genes confirmed our previous 16S rRNA-based analysis15 (Supplementary Methods, Supplementary Table 1). Particularly, feeding B. infantis EVC001 increased Bifidobacteriaceae abundance in feces of breastfed infants, whereas no B. infantis was detected among control samples. After two weeks of supplementation, Bifidobacteriaceae was significantly increased (p = 7.18E-07), whereas Enterobacteriaceae (p = 0.0001) and Clostridiaceae (p = 0.007) families were significantly decreased (Fig.1A). To

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profile the VF gene composition in samples, we used a non-redundant database obtained by merging three well-known VF gene databases (Supplementary Methods). A total of 2,832 VF genes were identified in controls, representing nearly twice the number of VF genes identified in EVC001-fed infant samples (Supplementary Table 2), which contained significantly fewer VF genes (p = 0.0001). On average, EVC001-fed infant samples had an 85% lower relative abundance of VF genes in the overall metagenome than control samples (Fig. 1B). Hierarchal clustering based on the overall abundance of VF gene profiles revealed a marked separation of the individual samples based on supplementation status (Fig. 2A). This suggested similarities in VF type and respective abundances in samples within the same treatment group, with the majority of those in the EVC001-fed group clustering with the lower VF gene abundance (Fig. 2A). Furthermore, 146 individual VF genes were lower in the EVC001 group (FDR-p < 0.05). These genes were mapped to the corresponding KEGG orthologs and pathways (Fig. 2B). Contextually, many of the gene functions in the database identified in samples from EVC001-fed infants as virulence factors are housekeeping genes that are necessary but not sufficient, or are repurposed from their known housekeeping function, for infection by pathogenic bacteria16. Conserved among the genes for many of the potentially pathogenic organisms identified were those for glutathione reductases, arginine Nsuccinyltransferases, stress response regulators (Hsp90, OmpR/EnvZ, rpoS), Fe (III) and Zn permeases, and flagellar proteins (FliN/FliY) (Supplementary Table 3). These gene functions are all associated with response to stress. Host inflammation creates an environment that favor certain taxa who thrive under differentially oxidative states17, 18, and a picture of inflammation and dysbiosis is emerging based on this understanding19. Although ideal for functional classification, VF databases are usually built with genes identified in model organisms, thus limiting taxonomic classification. To infer the proper taxonomic assignment of bacteria contributing to the identified VFs, we performed individual metagenome assemblies of five representative samples with the most abundant and diverse VF gene profiles (Supplemental methods). Assembled metagenomes were converted into local databases used to retrieve taxonomic information coupling previously identified clade-specific VFs amino acids sequences. Higher levels of Bifidobacteriaceae (i.e., B. infantis) were associated with a lower abundance of VFs, whereas higher abundance of Enterobacteriaceae (e.g., Escherichia coli, Klebsiella), Clostridiaceae (e.g., Clostridium), Pasteurellaceae (e.g., Haemophilus), Staphylococcaceae and Streptococcaceae families, as well as different potential pathogens belonging to the Proteobacteria and Firmicutes phyla, were related to a higher abundance of VFs (Fig. 2C). Multivariate linear modeling identified associations between supplementation status and global relative abundance of bacterial species.

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Particularly, Haemophilus parainfluenzae, Escherichia coli and Streptococcus mitis were significantly higher in controls. Bifidobacterium longum was significantly increased in the EVC001-supplemented group (Fig 2, D). This is the first study using shotgun metagenomic sequencing to report a direct effect of VF gene reduction in the infant gut bacterial community via targeted probiotic supplementation. Colonization of breastfed infants with B. infantis EVC001 may offer an attractive approach to reduce the number of VFs and the relative abundance of potential pathogenic gut bacteria that harbor them. Future work will be needed to determine whether colonization by B. infantis EVC001 relates to increased resilience in the face of pathogen challenges. Ethics approval and consent to participate The study was conducted under the approval of the University of California, Davis Institutional Review Board and registered at ClinicalTrials.gov under study NCT02457338. All experiments were performed in accordance with relevant guidelines and regulations. Consent for publication Consent for participation and publication of the study results was obtained from subjects or their legal guardians. Availability of data and material Human filtered sequencing libraries were deposited on the Sequence Read Archive (SRA; https://www.ncbi.nlm.nih.gov/sra) with number PRJNA390646. Conflict of interest GC and SAF are employed by Evolve BioSystems, Inc., Davis California. Authors' contributions GC and SAF contributed to the study design, experimental design and conducted the analysis. All authors contributed to writing, editing and approving the manuscript. Funding The study was funded by Evolve BioSystems, Inc., Davis, California. Competing Interests Statement Dr. Giorgio Casaburi and Dr. Steven Frese are employees of Evolve Biosystems, which funded the study.

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Acknowledgements This work used the Vincent J. Coates Genomics Sequencing Laboratory at UC Berkeley, supported by NIH S10 OD018174 Instrumentation Grant. The authors thank Cora Morgan for technical editing of the manuscript. Supplementary Data Appendix A. Supplementary Methods Appendix B. Supplementary Table 1. Taxonomic relative abundance at all classification levels. Appendix C. Supplementary Table 2. Virulence factor relative abundance in each sample Appendix D. Supplementary Table 3. KEGG ortholog functional assignments at the genus level by sample. Figure Legends Fig. 1A) Average relative abundance of top 10 bacterial families identified within the EVC001-fed and control groups. B) Average relative abundance of virulence factors in the entire metagenomes. (p < 0.0001, Mann–Whitney test).

Fig. 2A. Heatmap showing virulence factor (VF) abundance across samples in Reads Per Kilobase per Million mapped reads (RPKM). Samples were hierarchically clustered based on similar VF profiles and colored by treatment, with the p-value bar highlighting only significant VFs (p < 0.05; Kruskal–Wallis with FDR correction). B. Abundance among treatments (RPKM) of most significant VF (p < 0.05) mapped to 15 KEGG orthologs and 8 KEGG pathways. Higher frequencies are associated with pathway completeness based on gene presence. C. Relative abundance of bacterial families identified across samples. “Others” refers to several bacterial families for which individual relative abundance was lower than 1%. D. Differences in the gut microbiome composition at the species level between the EVC001-fed and control groups. Bar plot of γ-coefficients from multivariate association with linear models (MaAsLin) statistical analysis assessing associations between microbial species and supplementation status. Positive (teal bars) and negative (grey bar) coefficient values represent taxa enriched in the EVC001-fed group and the control group, respectively. Q-values are FDR-adjusted pvalues as computed by MaAsLin.

References 1

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6

B

Relative abundance (%) of bacterial families

100%

Relative abundance (%) of virulence factors (VFs)

A

Veillonellaceae

90%

Pasteurellaceae

80%

Streptococcaceae

70% 60%

Staphylococcaceae Enterococcaceae

50%

Porphyromonodaceae

40%

Clostridiaceae Enterobacteriaceae Bacteroidaceae Bifidobacteriaceae

30% 20% 10% 0%

Control

0.7%

EVC001

****

0.6% 0.5% 0.4% 0.3% 0.2% 0.1% 0%

Control

EVC001

A

EVC001

B

Control

Most Significant Virulence Factors (KEGG Orthology) K02911: large subunit ribosomal protein L32 K01875: seryl-tRNA synthetase K01893: asparaginyl-tRNA synthetase

1000 500 50 0

K03076: preprotein translocase subunit SecY K01696: tryptophan synthase beta chain

RPKM (Reads Per Kilobase per Million mapped reads)

2000

High abundance

K06204: DnaK suppressor protein K09816: zinc transport system permease protein K02417: flagellar motor switch protein FliN/FliY K07638: OmpR family, osmolarity sensor histidine kinase EnvZ K01716: 3-hydroxyacyl-[acyl-carrier protein] dehydratase K02011: iron(III) transport system permease protein K00383: glutathione reductase (NADPH) K00673: arginine N-succinyltransferase K03087: RNA polymerase nonessential primary-like sigma factor RpoS K05685: macrolide transport system ATP-binding/permease protein

RPKM 300

250

200

150

100

50

0

Most Significant Virulence Factors (KEGG Pathway) beta-Oxidation, acyl-CoA synthesis

Low abundance

Phosphate acetyltransferase-acetate kinase

C

100%

7056 7052 7019 7042 7086 7004 7021 7062 7020 7084 7067 7071 7079 7174 7014 7075 7028 7130 7016 7050 7149 7029 7046 7005 7055 7058 7023 7142 7040 7051 7074 7076 7122 7015 7035 7094 7006 7018 7032 7136 7072 7002 7054 7146 7022 7085 7053 7070 7068 7001 7064 7012 7007 7080 7140 7123 7087 7077 7025 7091

FDR adjusted P

Sec (secretion) system

90% 80%

Fatty acid biosynthesis, elongation

0.05

EnvZ-OmpR (osmotic stress response)

0.01

Ribosome, bacteria

0.001

Zinc transport system

10e-5

Iron(III) transport system

D

Frequency in significant pathway

10 9 8 7 6 5 4 3 2 1 0

Haemophilus parainfluenzae Haemophilus influenzae Shigella sonnei Klebsiella pneumoniae Klebsiella oxytoca Escherichia coli Enterobacter cloacae Enterobacter aerogenes Streptococcus mitis oralis pneumoniae Streptococcus parasanguinis Bifidobacterium longum

70% 60% 50% 40% 30% 20% 10% 0%

Bifidobacteriaceae

Bacteroidaceae

Enterobacteriaceae

Clostridiaceae

Porphyromonadaceae

Enterococcaceae

Staphylococcaceae

Streptococcaceae

Pasteurellaceae

Veillonellaceae

Others (n=26)

Coefficient

*

-0.2

Q-Value

* * -0.15

-0.1

-0.05

0

*

0.05

0.016 0.105 n/a 0.633 0.250 0.010 0.869 n/a 0.031 0.085 0.016