Giardia overcomes microbiota-mediated pathogen clearance during protein malnutrition, and combines with protein malnutrition to promote growth impairment, small intestinal 16S abundance, and altered mucosal immunity

Murine intestinal microbiota can differentially prevent prolonged Giardia lamblia colonization, even in T and B-cell deficient hosts. Thus, we and other investigators have used continuous antibiotics (ampicillin, vancomycin, neomycin) (Abx) in drinking water to enhance G. lamblia infection [18–21]. Using this Abx cocktail we previously published that G. lamblia (Assemblage B, strain H3 cysts) challenge results in detectable shedding at 10⁴−10⁵/gram feces by qPCR of the 18S small ribosomal subunit through the first 5–7 days post-challenge (early infection). But unlike clearance following G. lamblia (Assemblage A, strain WB trophozoites) challenge, G. lamblia H3 shedding increases by ~ 2 logs after day 9 and remains consistent through 4–6 weeks together with small intestinal trophozoite colonization (persistent infection) [18]. To test the hypothesis that the disrupted intestinal 16S community during protein malnutrition [16] would functionally impair microbiota-mediated colonization resistance [24], we eliminated Abx from the model. Weaned mice were fed either a protein deficient (2% protein) diet (PD) or an isocaloric but protein sufficient (20% protein) control diet (CD) for 15 days prior to challenge with 10⁶ G. lamblia H3 (Assemblage B) cysts (Fig 1A). We previously published that this duration of acclimation on diet is sufficient to establish discrepant 16S rRNA genetic profiles [16]. Small intestinal tissues harvested at 5 days (early) and 28 days (persistent) post-infection (dpi) demonstrated higher abundance of Giardia on day 5 in mice fed PD and only mice fed PD remained infected through 28 days by qPCR (Fig 1B). Histopathology confirmed the presence of mucosal-associated Giardia trophozoites in H3 cyst-challenged mice fed PD (Fig 1C). In separate experiments, we confirmed that parasites persisted in mice fed CD and challenged with 10⁶ G. lamblia H3 cysts if concurrently treated with Abx. Giardia was detected in the duodenum of abx-treated mice fed CD at 35 dpi, and regardless of diet, Giardia was detected in stools through 42 dpi (S1 Fig). Finally, consistent with the greater infectious potential of the partially stomach-acid resistant parasite cyst stage compared with the excysted trophozoite stage, we confirmed that regardless of Abx, only H3 cysts and not axenized H3 trophozoites were sufficient to achieve consistent Giardia colonization by both light microscopy and qPCR (S1 Fig) in this model.

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Fig 1. Protein malnutrition in weaned mice disrupts Giardia clearance, promotes increased microbial-pathogen abundance in small intestine, and establishes cytokine profiles associated with persistent Giardia infection.

(A) Experimental timeline of Giardia challenge in 3 week-old C56Bl/6 mice initiated on either control diet (CD) or protein-deficient diet (PD) upon arrival and continued throughout the duration of the experiment. G. lamblia (Assemblage B, H3) infection occurred on experimental day 0. Data for this and subsequent experiments were obtained during either early timepoints when mice on both diets remained infected with Giardia (day 5–7) or later timepoints (up to 28 days) (persistent) when only mice fed PD diet remained infected. (B) Duodenal Giardia burden at day 5 (left) and duodenal and ileal Giardia burden on day 28 (right) post-challenge in either CD or PD-fed mice and uninfected controls. (C) Histopathology of duodenum in infected mice fed PD diet (20x, H&E, arrows designate trophozoites). (D) Growth in mice (as % weight increase between day 5 and day 0). (E) Small intestinal bacterial abundance by total 16S rRNA universal primers and (F) quantification of the V3-V4 region amplification product. (G) Krona visualizations of 16S rRNA OTUs in the upper small intestine high-abundance taxa (>10,000 reads per OTU) in mice fed CD (left) or PD (right) 5 days after Giardia lamblia (bottom) compared with age and diet-matched controls (top) as indicated. (H) Phyla-level 16S rRNA relative abundances in upper small intestine 5 days after G. lamblia challenge compared with age and diet-matched controls. (I) Flow cytometry of duodenal lamina propria leukocytes (LPL) day 5 post-challenge, stained for leukocytes (CD45⁺) and frequency of myeloid (CD11b⁺), T- (CD3⁺) and B- (B220⁺) cells and (J) Cytokine protein levels in duodenum shown as fold change relative to uninfected CD-fed controls (PBS). For all studies n = 4/group; *P<0.05, **P<0.01.

https://doi.org/10.1371/journal.ppat.1006471.g001

Similar to what we observed previously in abx-treated mice [18], protein deficiency combined with Giardia to impair host growth (P<0.05 PD-Giardia vs uninfected CD-fed control in Fig 1D). Giardia infection in mice fed a PD diet also had greater duodenal bacterial abundance, measured by both universal 16S rRNA qPCR/gram tissue and V3-V4 specific amplicon product, than infected mice fed CD (P<0.05) (Fig 1E and 1F). Consistent with several features of microbial alterations in both malnourished children [25] and protein-deficient diet fed mice [26], the duodenal 16S rRNA composition in mice fed PD demonstrated an increased Firmicutes:Bacteroidetes ratio (S1 Fig) that was mainly driven by an increase in the abundance of Clostridiales (Fig 1G). Giardia tended to enhance this skew towards Firmicutes together with a reduction in Bacteroidetes from 12%—7% (Fig 1H). Thus, rather than excluding Giardia, the small intestinal microbiota in mice fed the protein deficient diet permitted persistent Giardia infection whereas abx were necessary for prolonged parasite detection in mice fed the CD diet.

To examine whether PD in this model had interfered with protective mucosal responses against Giardia we performed flow cytometry on upper small intestinal lamina propria in the same mice. Regardless of infection, mice fed PD demonstrated a skew toward increased myeloid cells (CD11b⁺) with reciprocal reductions in T-cells (CD3ε⁺) among CD45⁺ cells analyzed compared with mice fed the CD-diet (Fig 1I). In addition, mice fed PD demonstrated a reduction in B-cell frequency (B220⁺) at 5 dpi compared with infected mice fed CD (P<0.05) (Fig 1I). Concurrently, we analyzed mucosal production of key cytokines that promote Giardia clearance, such as IL-6 and IL-17A [27, 28], compared with those that resembled the profile of prolonged infections in children (increased IL-4) [28] (Fig 1J). Corresponding to persistent infection, mice fed PD demonstrated a trend toward decreased IL-6, IL-17A, and IL12p40, with a significant increase in IL-4 (P<0.05 for IL-4), irrespective of Giardia infection.

Intestinal microbiota determine growth outcomes during giardiasis

Having established that Giardia incorporates into a disrupted intestinal microbiota in mice fed the PD diet, we next investigated the role of resident microbiota as determinants of growth impairment during Giardia infection in PD diet fed mice (Fig 2A). Continuous exposure to the antibacterials that have no anti-giardial activity (Abx) prevented Giardia-induced growth impairment (Fig 2B) even despite an early increase in Giardia fecal shedding (Fig 2C) and a similar intestinal Giardia burden through 14 dpi (Fig 2D). The Abx exposure resulted in a fecal dominance of Lactococcus (>98%) regardless of infection (Fig 1S). In non-Abx treated mice, there were no significant differences in fecal 16S rRNA composition between infected and non-infected mice (Fig 2E), although Enterobacteriaceae tended to be over-represented in Giardia infected mice (Fig 2F). Targeted qPCR to determine absolute abundance of predominant taxa (Firmicutes and Bacteroidetes) as well as Enterobacteriaceae identified reductions in both Firmicutes and Bacteroidetes to below the limit of detection in the duodenum and 3–4 log decreases in the feces during Abx treatment regardless of infection (Fig 2G).

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Fig 2. Giardia interacts with resident microbiota to impair host growth during protein malnutrition.

(A) Experimental timeline. 3-week-old C57Bl/6 mice were initiated on the PD diet upon arrival. Antibiotic (Abx)-treated animals received antibiotics vancomycin, neomycin, and ampicillin continuously ad libitum in drinking water beginning 8 days prior to G. lamblia challenge and throughout the duration of the experiment. (B) Growth curves of each experimental group as percent of initial weight beginning on the day of G. lamblia challenge (Day 0). **P<0.01, *** P<0.001 (G. lamblia vs. PBS); ^P<0.05, ^^^P<0.01, ^^^^P<0.001 (G. lamblia vs. PBS^Abx), and ^## P<0.01 and ^#### P<0.0001 (G. lamblia vs. G.lamblia^Abx) (n = 11-13/group in combined replicate experiments). (C) Effect of continuous antibiotics on serial Giardia fecal shedding and (D) day 14 duodenum burden as determined by 18S qPCR. (E) Krona visualization of fecal 16S V3-V4 OTUs in PBS control (left) and G. lamblia infected (right) mice at 14 days post-challenge. (F) Fecal Enterobacteriaceae abundance by 16S V3-V4 OTUs in PBS and G. lamblia (G.l.) infected mice at 14 days post-challenge. (G) Abundance of Firmicutes, Bacteroidetes and Enterobacteriaceae by qPCR in duodenum (left) and feces (right) day 14 after G.lamblia challenge (*P<0.05, ****P<0.0001), ^#P<0.05, ^{^}P<0.05 as indicated (n = 4 = 8/group). (H) Correlation between growth as % weight change at 14 days after G. lamblia challenge (such that 0 = no change in weight and 15 = 15% weight increase) and fecal qPCR abundance of designated bacterial taxa or G. lamblia in uninfected (left) and G. lamblia challenged mice (right).

https://doi.org/10.1371/journal.ppat.1006471.g002

In non-Abx treated Giardia-infected mice there was a 1.5 log increase in Firmicutes (P<0.05) in the duodenum (Fig 2G). In addition, consistent with findings that increased numbers of E. coli in small intestinal aspirates recovered from patients with giardiasis correlate with greater symptom severity [29], increased fecal Enterobacteriaceae abundance at 15 dpi in non-Abx treated mice was a better predictor of poor growth in individual Giardia-infected mice than Giardia burden in either stool or duodenum (Fig 2H).

Giardia combines with EAEC to worsen malnutrition and both pathogens contribute to altered mucosal immune responses during co-infection

To test whether alterations in intestinal microbiota and mucosal immune responses during persistent Giardia infection would enhance or diminish growth impairment during enteropathogen co-infection, we next developed a sequential co-infection model using one of the most common pathogen isolated in malnourished children, EAEC [10]. For these experiments we used EAEC042 that elicits acute myeloid cell inflammation during other nutrient deficient states [17]. First, we established that challenge with 10⁹ EAEC042 in mice fed the PD diet but not mice fed CD diet led to rapid weight loss (7% body weight compared with uninfected PD-fed controls (P<0.001 3 dpi) (Fig 3A) and mucosal inflammation that persisted through 14 days post-EAEC challenge (Fig 3B). Next, we acclimated mice on either the PD or CD diet for 15 days prior to Giardia exposure and then sequentially challenged with EAEC042 during the persistent phase (14 dpi) of Giardia infection (Fig 3C). The two pathogens combined to enhance weight loss in mice fed the PD diet (~100% greater loss of initial weight, P<0.05 in co-infected mice compared with uninfected PD-fed controls) (Fig 3D). In mice fed CD and co-infected with both pathogens, no weight loss was observed (Fig 3D). Giardia did not influence EAEC042 stool shedding which was 2 logs greater in mice fed the PD diet as determined by qPCR of the EAEC-specific aap target (Fig 3E).

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Fig 3. Giardia and EAEC combine to worsen growth during protein malnutrition and persistent Giardia infection alters intestinal immune responses to EAEC.

(A) Impact of 10⁹ EAEC042 challenge on growth (% initial weight) of PD-fed and CD-fed mice compared with PD-fed uninfected controls (Day 0 = 28 days on diet) (n = 4/group; *P<0.05 PD-PBS vs CD-EAEC day 3; ***P<0.001 and ****P<0.0001 PD-EAEC vs PD-PBS day 2 and day 3). (B) Flow cytometry of ileum lamina propria leukocytes (CD45+) through 14 days post-EAEC infection (n = 4/group; *P<0.05). (C) Experimental timeline for persistent G. lamblia-EAEC co-infection challenge model. 3-week-old C57Bl/6 mice were initiated on either the PD or the CD diet upon arrival and for 15 days prior to G. lamblia challenge. Sequential challenge with EAEC occurred during persistent (d 14) G. lamblia infection. (D) Impact of prior Giardia exposure on growth following EAEC co-infection. Depicted is growth through 3 days after EAEC co-infection (32 days on diet, 17 days after Giardia infection) (n = 4 per group (CD diet groups) and 6-17/group (PD diet groups); ***P<0.001 PD uninfected vs. either CD-EAEC or CD-G.lamblia-EAEC; *P<0.05 PD-G. lamblia-EAEC vs. PD uninfected) (E) EAEC shedding on day 1 and day 5 post-challenge in CD or PD-fed mice either with or without prior Giardia exposure as indicated. (n = 4/group; *P<0.05 as indicated). (F) Luminal inflammatory biomarkers (Myeloperoxidase (MPO), Calprotectin, and Lipocalin-2) depicted as fold change relative to PBS uninfected controls 3 days after EAEC and 13 days after G. lamblia challenge (n = 7-13/group). Data to the right of the dashed line in all groups represents differences dichotomized to whether mice received G. lamblia challenge (any Giardia challenged, combined) or not (not Giardia challenged, combined) (n = 12-24/group). Data for fecal MPO also includes two individual combined experiments, at 13–17 days after Giardia and 3–7 days after EAEC (n = 7-13/group). (G) Flow cytometry of ileum lamina propria leukocytes (CD45+), and proportions of myeloid (CD11b+), T- (CD3+) and B- (B220+) cells 3 days after EAEC042 challenge (17 days after G. lamblia challenge) in PD-fed mice as indicated (n = 4-8/group; *P<0.05 (EAEC vs PBS), **P<0.01 (Giardia-EAEC vs PBS). Data is shown as fold change relative to uninfected PBS controls. (H) Flow cytometry of ileum lamina propria (left) leukocytes (CD45⁺), (middle) proportion of myeloid (CD11b⁺), T- (CD3⁺) and B- (B220⁺) and (right) eosinophils (Siglec-F⁺CD11b⁺) and CD4⁺ T-cells at 14 days after EAEC042 challenge (28 days after G. lamblia challenge) in PD-fed mice as indicated. (I) Intestinal protein levels 3 days after EAEC042 challenge (17 days after G. lamblia) in PD-fed mice. 29 of Luminex 32-target panel results shown in heatmap. Data depicted as fold change relative to uninfected controls (range 0.01 to 100). (*P<0.05 for Giardia, ^P<0.05 for EAEC, and #P<0.05 for Giardia-EAEC vs uninfected controls, n = 6-12/group).

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Giardia, however, did alter inflammatory markers of environmental enteropathy when present alone and during EAEC co-infection in protein deficient fed mice. Myeloperoxidase (MPO) a product of activated neutrophils, was variably detected in the mice fed protein deficient. Fecal MPO tended to be elevated in response to either pathogen alone, but paradoxically decreased to levels similar to uninfected controls in co-infected mice (Fig 3F). Calprotectin (Cp), another marker of myeloid cell activation, was elevated only in EAEC042 mono-infected animals, but was decreased in any Giardia infected group (Fig 3F). Lipocalin-2 (LCN), a marker of either neutrophil or epithelial cell activation was elevated only in Giardia-infected mice regardless of EAEC co-infection.

Immune responses in the mucosal compartment were also altered in persistent Giardia infected mice later challenged with EAEC. EAEC infection led to significant increases in myeloid lineage (CD11b⁺ cells) in the ileum at 17 dpi Giardia challenge and 3 dpi EAEC challenge (Fig 3G). The increased proportion of lymphocytes (both CD3ε⁺ and B220⁺ cells) at 28 dpi Giardia challenge and 14 dpi EAEC challenge (Fig 3H) was similar in either EAEC mono-infected or co-infected mice. In contrast, total LPLs, particularly lymphocytes (CD3ε+ and B220+ cells) were decreased during persistent (17 dpi) Giardia infection compared with uninfected controls (S2 Fig). Using a broad-based luminex 32-plex panel we performed an unbiased analysis of cytokine and chemokine responses on all protein deficient diet fed mice at 17 dpi Giardia challenge and 3 dpi EAEC challenge. We detected 28 of 32 targets in at least 2 mice in each group that are shown as fold change relative to uninfected controls (Fig 3I). Both pathogens modulated the cytokine/chemokine response alone and during co-infection. In all conditions, IL1α, a pro-inflammatory alarmin that is released by enterocytes during intestinal injury [30], was elevated in all groups and reached significance in Giardia infected mice (~30-fold) and robustly increased in co-infection (~80-fold). IL-9 was significantly elevated in Giardia mono-infected and by ~20-fold in co-infected mice, together with a tendency towards greater IL-4 and IL-13. Each group demonstrated a decrease in IFNγ, that was significant in EAEC mono-infected mice. CCL5 was elevated (~2 fold) in EAEC infected and co-infected mice. Consistent with the early expansion of myeloid cells in EAEC infected mice, CXCL8 (IL-8/KC) was also elevated in EAEC and co-infected mice (~1.6 fold). CCL11 (eotaxin) was uniquely elevated (~6-fold) only in co-infected mice. This change corresponded to a trend toward increased eosinophils (CD45⁺SiglecF⁺) among myeloid cells in co-infected compared with EAEC mono-infected mice (52% vs 39%, ns) at later timepoints (Fig 3H). Changes in select cytokines and chemokines in Giardia mono-infected mice from early (5 dpi) to persistent (17 dpi) timepoints compared with uninfected controls revealed alterations in mucosal immune responses during persistent Giardia infection. Giardia lead to progressive increases in IL-1α (P<0.05) and IL-2 (P<0.05) as well as IL-4 and IL-13, but IFNγ progressively decreased (P<0.05) in persistently infected mice (S2 Fig).

Co-infection enhances gut microbial host proteolysis and abolishes energy regulatory compensatory responses during malnutrition

To determine whether either pathogen alone or the pathogens in combination altered gut microbial host metabolism, we performed 16S rRNA sequencing in feces simultaneously with urinary metabolic profiling (metabonomics) using ¹H nuclear magnetic resonance (NMR) spectroscopy in mice fed the PD diet (Fig 4). In this experiment, weaned mice were highly susceptible to weight loss following 10⁶ G. lamblia H3 cyst challenge, that was further potentiated following EAEC co-infection six days later (Fig 4A). Focusing first on 16S rRNA sequencing, in Giardia mono-infected mice, phyla-level changes at day 7 and day 13 showed consistent relative increases in Firmicutes and reductions in Verrucomicrobia (Akkermansia mucinophila) in Giardia mono-infected mice (Fig 4B). Anaerobes such as Clostridiales members (day 7 and day 13 after G. lamblia challenge) and Turicibacter (day 7 after G. lamblia challenge) as well as Enterococcus sp. (day 13 after Giardia challenge) accounted for the Firmicutes expansion in Giardia mono-infected mice (S3 Fig). Either Giardia or EAEC mono-infected mice had a reduction in Bifidobacterium pseudolongum. In EAEC mono-infected or co-infected mice Enterobacteriaceae were increased relative to uninfected controls or Giardia mono-infection (S3 Fig). Phyla-level 16S rRNA composition in co-infected mice otherwise more closely resembled EAEC mono-infection.

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Fig 4. EAEC combines with Giardia to enhance microbial host co-metabolic perturbations and co-infection exhausts regulatory host energy expenditure adaptations during malnutrition.

C57Bl/6 males were initiated on the protein deficient diet upon arrival at 3 weeks of age and then challenged with G. lamblia 7 days later. Six days after G. lamblia, two groups were challenged with enteroaggregative E. coli (EAEC). Uninfected controls received PBS-PBS sham gavages at each infection timepoint. (n = 6/group). (A) Depicted is growth as percentage of starting weight beginning on the day of G. lamblia infection (Experimental day 0 (Day 0)) and through 13 days after Giardia challenge (7 days after EAEC challenge) (Day 13). (⁺P<0.05, ⁺⁺P<0.01, ⁺⁺⁺⁺P<0.001 Giardia-PBS vs PBS-PBS; ^#P<0.05, ^####P<0.001 Giardia-PBS vs PBS-EAEC; *P<0.05 Giardia-EAEC vs. Giardia-PBS Day 7 and Day 13; ****P<0.0001 Giardia-EAEC vs. PBS-EAEC Day 7 and Day 13). (B) Phylum-level relative operational taxonomic unit (OTU) abundances determined after amplification and sequencing of the V3-V4 region of 16S rRNA gene in fecal samples from uninfected, Giardia-infected, EAEC-infected, and co-infected mice on experimental days 7 and 13 as indicated. (C,D) OPLS-DA correlation coefficient plots indicating the variation between (C) Giardia infected (Day 13) and uninfected PBS controls (Day 13) (Q²Y = 0.40; P = 0.02) or (D) co-infection (Day 13) versus EAEC mono-infection (Day 13) (Q²Y = 0.82; p = 0.001) (n = 4-5/group). Correlation coefficients plots were generated with the use of a back-scaling transformation to display the contribution of each metabolite to the sample classification. Positive peaks indicate metabolites that were excreted in greater amounts in the Giardia infected (C) or co-infected (D) mice, and negative peaks indicate metabolites that were excreted in lower amounts. The color scale represents the significance of the correlation for each metabolite to the class membership with red indicating stronger significance and blue indicating weaker significance. (E) Heat map of significant changes in urinary metabolites measured using 1H NMR spectroscopy associated with OPLS-DA models. Represented as correlation coefficients (R) (red = increased; blue = decreased) in G. lamblia (Gl) infection at Day 7 and Day 13 versus age-matched uninfected (PBS) controls, EAEC mono-infection Day 13 versus age-matched uninfected (PBS) controls, or co-infection (Gl+EAEC) Day 13 compared with age-matched uninfected controls (PBS) or either mono-infection alone. Abbreviations: 2-OG, 2-oxoglutarate; 3-IS, 3-indoxylsulfate; 3-UPA, 3-ureidopropionic acid; 4-HPA, 4-hydroxyphenylacete; 4-CG, 4-cresolglucuronide; 4-CS 4-cresyl sulfate; DMA, dimethylamine; BG, butyrylglycine; GPC, α-glycerophosphocholine; HG, hexanoylglycine; IAG, indole acetyl gulconate; IVG, isovalarylglycine; MA, methylamine; m-HPPS, m-hydroxyphenylpropionylsulfate; NAG, N-acetyl glutamine; NAO, nicotinamide-N-oxide; NMND, N-methyl- nicotinamide; PAG, N-phenylacetylglycine; TMA, trimethylamine; TMAO, trimethylamine-N-oxide; UK, unknown.

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Orthogonal projection to latent structures-discriminant analysis (OPLS-DA) coefficient plots identified a range of urinary metabolic perturbations induced by Giardia infection on both day 7 and day 13 (Fig 4C) (Q²Y = 0.40; P = 0.02 vs uninfected PBS controls) many of which were also elevated in co-infected compared with EAEC mono-infected mice (Q²Y = 0.82; p = 0.001) (Fig 4D). We observed no significant difference in the OPLS-DA metabolic profiles of Giardia infected mice between day 7 or 13 days post-challenge (Q²Y = 0.33 R²X = 0.24, P = 0.12). Significantly altered metabolites are summarized in a heat map in Fig 4E along with their correlation to class membership. Focusing first on metabolites unique to Giardia infection (Fig 4E), consistent with Giardia trophozoite reliance upon on host-derived lipids for membrane synthesis and optimal growth (ie. lecithin, gylcocholic and taurocholic bile) [31], Giardia-infected mice demonstrated increased excretion of bile acid constituents, phosphatidylcholine (PC) coupled with choline breakdown metabolites methylamine (MA) and dimethylamine (DMA) and the taurine metabolite isethionate. These indicators of bile acid deconjugation and lipid breakdown were present on both day 7 and day 13 post-Giardia challenge (Fig 4E). Increases in MA and DMA occurred independent of a concurrent increase in the microbial-dependent precursor trimethylamine (TMA) or its hepatic oxidized metabolite TMAO, a biochemical pattern resembling that observed with Kwashiorkor-type malnutrition [1], and were thus suggestive of increased choline availability in the small intestine rather than downstream gut microbial-dependent choline breakdown. Alanine, a by-product of Giardia glucose fermentation, was elevated at day 13 post-Giardia challenge in mono-infected mice, while pipecolic acid, one of the most abundant amino acid byproducts of Giardia metabolism in vitro [32] was identified in Giardia-infected mice at both timepoints, regardless of co-infection. Giardia also enhanced gut microbial-host co-metabolites of aromatic amino acids including tyrosine (4-cresol glucuronide (4-CG) and 4-cresyl sulfate (4-CS) and 4-hydroxyphenylacetyl (4-HPA) sulfate), tryptophan (3-indoxyl sulfate (3-IS) and indole-3-acetylglycine (IAG)), and phenylalanine (phenylacetylglycine (PAG)). Increases in urinary β-oxidation metabolites, accumulation of the early tricarboxylic acid cycle intermediate cis-aconitate, and changes in muscle metabolites creatine and creatinine indicated altered host energy utilization in Giardia-infected mice. In addition, methylated nicotinamide derivatives capable of regulating energy expenditure (N-methylnicotinamide (NMND) and nicotinamide-N-oxide (NAO)) [23] were increased in Giardia infected mice. Consistent with the finding that increased urinary NMND predicts catch-up growth in undernourished children [7], persistently Giardia-infected mice fed the protein deficient diet developed ‘overshoot’ growth gains compared with uninfected age and diet-matched controls upon re-nourishment (switched from the PD to the CD diet on 42 dpi) (S3 Fig).

The Giardia-induced changes in gut microbial host co-metabolites of proteolysis either persisted (4-HPA sulfate, IAG) or overlapped (PAG, 4-CG, 4-CS) with those seen during EAEC infection alone, and these metabolites were even further magnified in co-infected mice (Fig 4E). However, EAEC-mediated increases in TMA and TMAO (Fig 4E), indicative of microbial-dependent choline breakdown, were reversed in Giardia co-infected mice (Fig 4E), and resembled the metabolic perturbation in choline metabolism of Giardia infection alone (Fig 4E). Similarly, elevated taurine excretion in Giardia- infected mice persisted through co-infection (Fig 4E). Whereas either infection increased lipid oxidation evident in increased β-oxidation breakdown products (hexanoylglycine, butyrylglycine, and isovalarylglycine) along with the β-oxidation pathway precursor acetyl-carnitine, metabolism during co-infection shifted away from β-oxidation as indicated by a decrease in acetyl-carnitine and downstream β-oxidation metabolites. Concurrently, co-infection led to an inversion of creatine:creatinine ratios, suggesting altered muscle metabolism compared with either infection alone (Fig 4E). Finally, host energy expenditure adaptations via the nicotinamide pathway (NMND and NAO) during Giardia infection alone (Fig 4E) were extinguished following EAEC co-infection (Fig 4E).

Ethics statement

This study included the use of mice. This study was conducted in strict accordance with recommendations in the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health. The protocol was approved by the International Animal Care and Use Committee at the University of Virginia (Animal Care and Use Committee Protocol number: 3315). Tissue procurement was performed following anesthesia (ketamine hydrochloride and xylazine) and cervical dislocation, and all efforts were made to minimize suffering.

Animals and malnutrition

All experiments were performed using weaned male C57Bl/6 mice received from Jackson Laboratories at 3 weeks of age. Mice were initiated on either a protein deficient diet (PD; 2% protein, Harlan Laboratories or Research Diets) or an isocaloric control diet (CD; 20% protein, Harlan Laboratories or Research Diets) within three days of arrival (24 days of life). For all experiments mice were randomized into weight-matched groups and continued on experimental diets throughout the duration of the experiment. Mice receiving continuous antimicrobials received ampicillin (1 mg/mL, Fischer), vancomycin (1 mg/mL, Novaplus), and neomycin (1.4 mg/mL, Durvet) in drinking water changed ad libitum or every five days. Serial weights were obtained every 1–7 days from arrival through the termination of the experiment. Stools were collected every other day following infection [18].

Giardia lamblia and enteroaggregative Escherichia coli preparations

Gerbil-passaged purified G. lamblia H3 (Assemblage B) cysts were purchased from Waterborne, Inc. (New Orleans, LA). Cysts were washed and diluted in PBS and used within 48 hours of arrival. Each infected mouse received an inoculum of 10⁴−10⁶ cysts. G. lamblia H3 trophozoites were also obtained from Waterborne, Inc and maintained in modified TYI-S-33 media prior to inoculum preparation (10⁷/mouse) as previously described [18]. The EAEC strain 042 was originally obtained from James Nataro at the University of Virginia. For each experiment, a separate inoculum of 10⁹/mouse was grown from a glycerol stocked maintained at -80°C and prepared in DMEM high glucose medium as previously described [17]. All pathogen preparations were maintained on ice until administered via oral gavage using 22-gauged feeding needles in 100 μL volumes. Uninfected controls were similarly gavaged with either 100 μL of PBS (for Giardia) or DMEM high glucose (for EAEC) control.

Ex vivo enumeration of Giardia trophozoites

At the time of euthanasia, 4-cm segments of small intestine were removed beginning 0.5 cm from the pyloric sphincter, and placed into 4-mL of chilled PBS on ice for 30 minutes. Trophozoites were identified using an inverted microscope and counted on a hemacytomer with a limit of detection of 10⁴ trophozoites/mL.

DNA extraction for pathogen and microbiota detection

DNA from stool and/or intestinal tissue was extracted from thawed samples using the QIAmp DNA stool Kit (Qiagen) as previously described [18]. For detection of 16S rRNA genes, modifications to enrich detection including additional steps of homogenization in bead tubes (UltraClean fecal DNA bead tubes, Mo Bio Laboratories) in 400/360μL of ASL/ATL buffer using a Mini-Beadbeater for 1 minute, 30/40 μL of Proteinase K for stool/tissue homogenates, and incubation of tissues at 56°C for two hours [70].

Real-time polymerase chain reaction for Giardia lamblia and EAEC quantification and bacterial group targets

See S1 Table for a list of gene targets used in this study. For all qPCR studies, a standard curve serial dilution for the respective target was run in replicate on all plates for validation purposes. A run was considered valid only if the BioRad CFX Detection System detected an efficiency of 90–110% and a correlation r² > 0.98. Both experimental (i.e. infected animal fecal DNA) and controls (i.e. uninfected animal fecal DNA) were run on the plate. A non-template control was universally included on every plate to control for non-specific amplifications.

Giardia lamblia and EAEC

Quantification of G. lamblia and EAEC infections and bacterial group targets (see bleow) were performed in a BioRad CFX Detection System by interpoloating C_t values of each run with a standard curve of known amounts of each respected pathogen DNA and transformed into number of organisms per milligram of sample [17, 18]. Development of these assays included spiking known quantities of pathogen into uninfected mouse stool as well as serial dilutions demonstrating no significant evidence of inhibition in the assay [17, 18]. The master mix solution and conditions for specific target detection of G. lamblia 18S small ribosomal subunit [forward primer, 5’- GACGGCTCAGGACAACGGTT-3’ (Operon), reverse primer, 5’- TTGCCAGCGGTGTCCG-3’ (Operon), and probe FAM-5’- CCCGCGGCGGTCCCTGCTAG-3’-BHQ (IDT))] and the EAEC aap gene (forward 5’-CTTGGGTATCAGCCTGAATG-3’ and reverse 5’-AACCCATTCGGTTAGAGCAC-3’ primers) for EAEC detection are described elsewhere [17, 18]. Amplification for G. lamblia consisted of 3 minutes at 95°C, followed by 39 cycles of 15 seconds at 95°C, and 60 seconds at 58°C. Amplification for EAEC consisted of 3min at 95°C, followed by 40 cycles of 10 seconds at 95°C and 30 seconds at 61.5°C, followed by 40 cycles of 10 seconds, starting at 65°C with 0.5°C increments for melt curve. For both pathogens, a standard curve ranging from either 10²⁻10⁷ G. lamblia cysts (determined by hemacytometer) [limit of detection 10³/1000 mg stool or tissue as previously described [18] or 10¹−10⁸ EAEC CFU/mL (determined by OD₆₀₀ and confirmed by plate counts), limit of detection 10¹/1000 mg stool or tissue as previously described [17] was included on every PCR run. For both pathogens, sample Ct values in the range of 37–40 and/or non-specific melt curves (EAEC) were considered non-specific and excluded from the analysis.

16S quantification of total bacteria, firmicutes, bacteroidetes, and Enterobacteriacea

The SYBR Green master mix solution and conditions for detection of Firmicutes, Bacteroidetes, and Enterobacteriacea are described elsewhere [70]. The Bact934 forward primer (5’- GGARCATGTGGTTTAATTCGATGAT -3’) and Bact106 reverse primer (5’- AGCTGACGACAACCATGCAG—3’) were used for Bacteroidetes detection; Firm350 forward primer (5’—GGCAGCAGTRGGGAATCTTC—3’) and Firm814 reverse primer (5’—ACACYTAGYACTCATCGTT—3’) were used for Firmicutes detection; and Uni515 forward primer (5’—GTGCCAGCMGCCGCGGTAA—3’) and Ent826 reverse primer (5’–GCCTCAAGGGCACAACCTCCAAG—3’) for Enterobacteriaceae detection. Amplification conditions consisted of 5 minutes at 95°C, then 40 cycles of 10 seconds at 95°C and 59°C for 30 seconds. Melt curve analysis was carried out in 0.5-degree increments for 5 seconds starting at 65°C and ending with 95°C. The Ct values on each run were compared to standards of known concentrations of bacterial DNA on the same plate as previously described [71]. For universal 16S detection, we used forward primer (5’ GTGSTGCAYGGYTGTCGTCA -3’) and reverse primer (5’ ACGTCRTCCMCACCTTCCTC -3’) [72]. and an Enterococcus faecalis with 4x16S copies/genome as a standard. For universal 16S detection (total bacteria), SYBR Green mastermix (Biolegend) was used with 10 ng of template DNA. Amplification conditions consisted of 2 minutes at 95°C, then 45 cycles of 15 seconds at 95°C and 50°C for 30 seconds and 72°C for 45 seconds. Melt curve analysis was carried out in 0.5-degree increments for 5 seconds starting at 65°C and ending with 95°C. Any Ct values between 37–40 and/or melt curves that did not align with the respective melt curve of the known bacterial DNA standards were considered non-specific amplification and excluded from analysis.

Total 16S V3-V4 library quantification, Illumina sequencing and data analysis

The V3-V4 region of the 16S rRNA gene was amplified according to manufacturer specifications (Ilumina Mi-Seq) from 5 ng of purified genomic DNA. Index primers (Nexterea XT Index 1 and 2) were used to label individual samples prior to library quantification. A pico-green assay was used to quantify individual sample libraries prior to normalization, pooling, and sequencing using Ilumina Mi-Seq. 16S libraries were pooled and sequenced using Ilumina MiSeq at the Microbiome Core at UNC or the Genomics Core Facility at UVA. Reads were assigned to samples using Illumina BaseSpace demultiplexing. From these reads, bacterial presence and relative abundance were quantified using the QIIME package, version 1.9.1 [73]. Fastq-join was called via QIIME to join paired-end reads with a minimum of 6 base pair overlap and 8 percent maximum difference [74]. Barcodes were extracted from paired reads, then reads were quality-filtered using split_libraries.py from QIIME with default parameters. Chimeric sequences were detected and removed using reference-based and de novo chimera identification with USEARCH61 [75] and the GreenGenes 16S rRNA database [75]. Identification of operational taxonomic units (OTUs) was performed by referencing the GreenGenes database with UCLUST (97% sequence identity cutoff) and de novo otu-picking with QIIME. The RDP classifier was used to assign taxonomy to identified OTUs. The weighted UniFrac distance [76] between each sample was calculated and principal coordinates analysis (PCoA) was performed on the resulting distance matrix. PCoA results were visualized with EMPeror [77]. To prepare OTU data for relative abundance comparisons, samples with fewer than 311 reads were excluded and OTUs were filtered by two criteria: being present in at least two samples and having 0.5% relative abundance in at least one sample. Using the remaining OTUs and their relative abundances, the DESeq2 package [78] was used, as implemented in QIIME, to determine differentially abundant OTUs. OTUs with a multiple-testing corrected p value <0.05 were considered differentially abundant.

For duodenal tissues there was a high degree of unassigned taxa. We therefore restricted the V3-V4 pipeline analysis to only those OTUs with at least 10,000 reads (“high-abundance”). This restriction resulted in 541,910 retained high quality reads in the duodenum (mean 15,483 reads/sample). 50–98% of otherwise unassigned taxa were successfully eliminated from these groups.

Metagenomic visualizations were generated using KRONA open source software (https://github.com/marbl/Krona/wiki)) after uploading OTU data files transferred to Krona ExcelTemplates (https://github.com/marbl/Krona/wiki/ExcelTemplate)) [79].

Urine metabonomoics ¹H NMR spectroscopy-based metabonomic analysis

Urine samples were on individual mice at each timepoint indicated. Sample collections occurred regularly at 2 pm on each collection data. Urines were placed immediately on ice, and stored at -80°C before shipping on dry ice to JMP and JS. Urines were then analyzed individually by ¹H nuclear magnetic resonance (NMR) spectroscopy. Each sample was prepared by combining 30 μl of urine with 30 μl of phosphate buffer (pH 7.4; 100% D₂O) containing 1 mM of the internal standard, 3-trimethylsilyl-1-[2,2,3,3-²H4] propionate (TSP). Samples were mixed by vortex and spun (10,000 g) for 10 minutes before transfer to a 1.7 mm NMR tube. Spectroscopic analysis was carried out on a 700 MHz Bruker NMR spectrometer equipped with a cryo-probe. Standard one-dimensional ¹H NMR spectra of the urine samples were acquired with water peak suppression using a standard pulse sequence. For each sample, 8 dummy scans were followed by 128 scans and collected in 64K data points. A recycle delay of 2 s, a mixing time of 10 μs and an acquisition time of 3.8 s was used. The spectral width was set at 20 ppm. Chemical shifts in the spectra were referenced to the TSP singlet at δ 0.0. Spectra were manually phased and corrected for baseline distortions. ¹H NMR spectra (δ 0.2–10.0) were digitized into consecutive integrated spectral regions (~20,000) of equal width (0.00055 ppm). The regions between δ 4.50–5.00 were removed in order to minimize the effect of baseline effects caused by imperfect water suppression. Each spectrum was then normalized to unit area. Multivariate modeling was performed in Matlab using in-house scripts. This included principal components analysis (PCA) using pareto scaling and orthogonal projection to latent structures-discriminant analysis (OPLS-DA) constructed using unit variance scaling. OPLS-DA models were constructed to assist model interpretation. Here, ¹H NMR spectroscopic profiles were used as the descriptor matrix and class membership (e.g. Giardia, EAEC, uninfected) was used as the response variable. The predictive performance (Q²Y) of the model was calculated using a 7-fold cross validation approach and model validity was established by permutation testing (1000 permutations) [16]. Metabolites associated with a series of pair-wise OPLS-DA models were identified by the correlation coefficient (R) with the class membership and summarized in a heat map.

Flow cytometry for lamina propria cells and luminex for cytokine and chemokine profiles

Flow cytometry of lamina propria cells was performed according to our previously published protocols [18]. For isolation of cells from ileum segments, suspensions of small intestinal lamina propria cells were prepared from 4 cm segments of distal small intestine beginning 1 cm from the ileocecal valve. After segments were PBS-flushed and cleaned of gross debris and mucus, they were incubated at 37°C in HBSS buffer containing 50mM EDTA and 1mM DTT for 30 minutes in a shaking incubator at 250 rpm in order to remove epithelial-layer cells. The digested tissue was passed through a 100-μm filter and the filtrate centrifuged as previously described [17]. For lamina propria cell isolations, the tissue pieces were minced and suspended in 10 ml RPMI media with 4% FBS containing 1.2 mg/ml collagenase Type IV, 1.0 mg/ml dispase, and 25–40 U/ml DNase I enzyme solution for 30 minutes at 37°C in a shaking incubator and strained through a 40-μm filter. The resulting pellets were resuspended in 1% BSA-PBS buffer. Fluorophore-conjugated purified mAbs used in flow cytometry were purchased from BD Biosciences (CD4-PE-Cy7, CD3ε-BV421, CD45-V500, and CD11b-APC-Cy7 (clone M1/70)) and Biolegend (B220 [CD45R]-PerCP), and cell surface staining was performed according to the manufacturer’s instructions. All samples were acquired on a CyAn ADP LX analyzer (BD Biosciences and Cytek Development). The leukocyte population was gated based on forward/side scatter, the threshold was set at 50 FSC and single cells isolated via pulse width. All gates were applied universally to all samples within each batch. Data is represented as number positive per normalized total events (i.e., 500,000) or frequency within a specified gate. This methodology was used to elucidate the proportional leukocyte changes in equal amounts of tissue [80]. Cell analysis was performed using FlowJo version 9.3.3 software (Tree Star).

For mucosal cytokine and chemokine responses, 0.5–1.0 cm of ileum were immediately placed in liquid nitrogen at the time of euthanasia and stored at -80°C until use. Protein was collected from ileum lysates, which were made using a lysis buffer containing 50 mM HEPES, 1% Triton X-100, and Halt protease inhibitor on ice and homogenized in Zirconia beads (Biospec) using a Mini-Beadbeater (Biospec) for 60 seconds. Clarified supernatants were stored at -80°C. Multiplex protein quantification was performed using Luminex 100 IS System at the University of Virginia Biomolecular Core facility.

Cecal/Fecal inflammatory marker measurement

Markers of inflammation were measured in the cecal contents or stool using methods described previously [5, 16]. Briefly, stool or cecal contents were collected when cecal and other intestinal tissue was harvested and stored at -20°C until measurement. At the time of analysis specimens were allowed to thaw at room temperature and were diluted 7-fold in buffer with protease inhibitors (RIPA, radioimmunoprecipitation assay buffer). The samples were vortexed, centrifuged and the supernatants used to measure the biomarkers. The fecal myeloperoxidase (MPO) and lipocalin-2 concentrations were measured using commercially available kits that employed polyclonal antibody-based enzyme-linked immunosorbent assay (ELISA) methods, from R&D systems (Minneapolis, USA) according the manufacturer’s instructions. Cecal calprotectin was quantified by ELISA (Hycult Biotech) according to manufacturer's instructions using 1:1000 dilution of cecal contents based on optimization using pooled cecal samples. Measured protein levels were normalized to total lysate protein for respective specimens as determined by bicinchoninic assay (BCA) (Thermoscientific) at 562nm absorbance (Biotek ELISA plate reader) after 30 minutes incubation of sample with reagent at room temperature. Total protein of each sample was assayed using the BCA Protein Assay Kit from Pierce (Pittsburgh, PA). The absorption was measured using an Epoch plate reader, Bio-tek Instruments, Inc. (USA). Units were expressed as pg/mg of total protein.

Statistical analysis

Data analyses were performed with GraphPad Prism 6.0 and 7.0 software. All statistical analyses were done from raw data with the use of One-way and Two-way analysis of variance with Dunn’s or Bonferroni post hoc analysis from multi-group comparisons. For comparisons between only two groups, Student t tests were used for parametrically distributed data and Mann-Whitney tests for non-parametrically distributed data where applicable. Differences were considered significant at P<0.05. Data are represented as means ± standard errors of the mean.