ITT analysis of effects across outcome variables showed reduction in Streptococcus count and improvement across multiple clinical outcomes with no clear sex difference in treatment effect. The clinical changes observed with this short intervention included large effects likely to reflect modest clinical improvement on some secondary sleep outcomes (wakefulness, efficiency, quality), primary and secondary cognitive outcomes (attention, processing speed, cognitive flexibility, story memory, verbal fluency) and total symptoms. Measures of mood, fatigue and d-lactate showed no (or low) treatment effects.

Improvement on some sleep and cognitive measures appear promising considering this short intervention (4-weeks) and the complexity of this chronic condition (average illness duration ~ 10 years). It is unclear whether clinical changes at post were a direct response to the treatment or better explained by placebo, practice effects (particularly cognitive outcomes) or symptom variability of unknown origin. If placebo effects are the primary explanation for the results observed, we would have predicted consistent improvements across subjective variables (i.e., sleep, mood and fatigue variables) that were not shown. With these confounding factors in mind, improvement on objective sleep parameters may provide the most reliable indicator of change. Using these conservative parameters, reduced wakefulness after sleep onset (actigraphic WASO) may be the best indicator of clinical improvement.

Unexpectedly, individual variability of treatment response was highlighted by the proportion of participants who increased in Streptococcus counts at post (count = 28%, RA aerobe = 41%, RA total = 31%). This prompted exploration of relationships between change in microbial count and clinical symptoms. Ancillary results showed that shifts in microbiota were associated with more of the variance in clinical changes for males compared with females. Smaller correlations for females may (i) suggest non-monotonic relationships, (ii) raise questions about the benefits of the intervention for this group, (iii) suggest that other unmeasured factors may contribute to the variance observed (i.e., changes in the microbiome, hormonal, immune, other stressors) or (iv) indicate an alternate mode of action in females (i.e., not revealed by the methods carried out in this pilot study).

In males, change in Bacteroides, Bifidobacterium and Clostridium were associated with change across several symptoms. Intercorrelations between change in microbial and clinical variables suggest that an increase in Bacteroides (count) was associated with improvement on some clinical measures of sleep, mood, fatigue and total symptoms. Similarly, increased Bifidobacterium was associated with improvement in sleep quality, general fatigue, anxiety and visual learning. For Clostridium, a reduction was associated with more clinical improvements (cognitive and total symptoms).

Previous findings suggest that it would be premature to conclude that these genera are only relevant for males with ME/CFS [26, 28, 68]. Armstrong et al. [68] found reduced frequency of Bacteroides and increased frequency of Clostridium in female ME/CFS patients compared with controls. Decreased Bacteroides spp. in ME/CFS compared with controls and positive associations with serum amino acids [68] may be particularly relevant considering the role of amino acids for cellular energy [69]. Nagy-Szakal et al. [26] also found reduced proportion of Bacteroides vulgatus but an increased abundance of ‘unclassified’ Bacteroides using sequencing techniques in ME/CFS patients without IBS symptoms. Prior evidence combined with our results raise questions about the abundance, diversity and functional role of Bacteroides in ME/CFS. Therefore, a more reasonable explanation for our ancillary results may be related to observed changes in our sample. For example, a larger proportion of males (11/16, 68.8%) increased in Bacteroides count at post compared with females (10/26, 38.5%). Rather than pointing to sex differences as a primary factor relevant for treatment response, our results could merely reflect individual variability or could imply increased complexity in females (i.e., the influence of other confounding factors such as hormonal shifts that may account for a larger percentage of the variance).

The growth in Bacteroides species at post for 11/16 males may have occurred from cross-feeding through probiotic supplementation. Metabolic by-products from one bacteria can become a food source (i.e., prebiotic) for other commensal bacteria [70]. Several Bifidobacteria species produce complex carbohydrates (exopolysaccharides) that can become substrates for other bacteria and subsequently promote their growth [70]. Some strains of Bifidobacterium have been shown to increase species of Bacteroides using culture methods ex vivo [70, 71]. Whilst the strains analysed in prior studies are not directly comparable to the strains administered in this study (B. lactis, B. breve, B. longum), the possibility of similar metabolic processes should be considered. Our increasing understanding of cross-feeding and microbial communication (see review [33]) may be useful to identify probiotic or prebiotic treatment alternatives to restore microbial homeostasis.

Relevance for d -lactate theory

The results of ITT outcome and ancillary analyses showing no change in d:l lactate ratio at post and small negative correlations between change in d:l lactate and Streptococcus, raise doubts about d-lactate metabolism from Streptococcal species. Considering, 21/38 participants increased in d:l lactate ratio after the intervention, it appears that the reduction of Streptococcus did not decrease d-lactate concentrations as expected. Given the enteric microbiota consists of more than 1000 species of bacteria [33], the limitations with culture-based identification methods, and the uncertainty around which species are producing lactate, it is possible that a reduction in Streptococcus may have allowed another d-lactate producing organism to proliferate. Some ancillary results provide partial support for d-lactate theory in males with change scores indicating decrease of d:l lactate ratio associated with improvement on some clinical outcomes (sleep onset (actigraphy SOL), mood disturbance (POMS), general fatigue (MFI), and total symptoms (SSH)). Perhaps our results reflect the relative change in reduced l-lactate production that would impact the ratio measured. Further research is needed to compare d-lactate concentrations (optimally in urine, faecal and serum samples) in ME/CFS with healthy controls and investigate other possible d-lactate producing bacteria, to adequately evaluate the relevance of the d-lactate hypothesis for either sex.

Limitations

Our interpretation of d:l lactate is restricted by methodological limitations requiring the use of a lactate ratio. The routine use of creatinine for normalising urinary metabolites [72] may be inappropriate considering findings of higher creatinine concentrations in ME/CFS patients compared with controls [50]. Without an appropriate method for normalisation, absolute d-lactate concentrations and absolute l-lactate concentrations could not be statistically analysed because of the known wide variation in the concentration of spot urine samples in contrast to 24 h timed collections used to calculate daily excretion rates. Similarly, using genera rather than species data for microbial outcomes has reduced specificity and restricts interpretation.

The open-label design without placebo-control and using repeated measures carries inherent limitations restricting interpretation and generalisability of findings. Whilst the placebo response appears to be lower in ME/CFS than other medical conditions (e.g., depression, migraine, gastro-intestinal conditions), the influence of participant expectation appears to be greater for interventions with physiological targets (i.e., infectious or immunological) compared with psychosocial interventions in ME/CFS [73]. Discrepancies between cognitive measures and other symptoms raise questions about the influence of practice effects inherent in repeated testing over a short interval. Whilst alternate forms and outcomes with reduced practice effects were prioritised (see Additional file 1: Additional Method), ideally, controlled comparison can be used in future research to ascertain the proportion of change that can be attributed to familiarity with cognitive tests.

Other confounding factors included the influence of diet, concurrent medication and fluctuating symptomatology. Whilst we attempted to control for these factors by asking participants to remain stable on their diet and medication, the possibility of effects from other treatments or dietary intake cannot be excluded. The nature of the condition is that it has symptomatology that can be exacerbated or diminished without clear attributional cause. These fluctuations and other environmental (change in education or employment status, family stressors) and/or physiological (e.g., stage of menstrual cycle, viral/bacterial exposure) factors could not be controlled.

Statistical limitations include reduced power with smaller male samples, consideration of multiplicity of analyses and restricted interpretation with correlations. Results from correlational data only provide information about monotonic relationships, cannot attribute causation and have limited capacity to infer direct treatment effects. Cautious interpretations have been made focusing on large effects to attempt to reduce bias and improve generalisability. However, this conservative approach excludes small and moderate correlations that may also be relevant.

Other modes of action

Some lactate results that contradict d-lactate theory prompt consideration of whether Streptococcus spp. or the intervention could have other modes of action. Streptococcal throat infections have been proposed as precipitating encephalitis and neurological symptoms in childhood (see [74–76]). Evidence of abnormal basal ganglia imaging and antibasal ganglia antibodies suggests that streptococcal infections may trigger autoimmune responses in some individuals [76]. Within the context of ME/CFS, it seems reasonable to explore whether the overgrowth of commensal enteric Streptococcus, as observed in 58/92 (59.2%) patients screened, may exert immunological or autoimmune effects that contribute to neurological symptoms. Future research could also evaluate a history of streptococci infections and monitor immune and inflammatory markers to establish whether similar mechanisms are at play in ME/CFS. Monitoring immune and inflammatory markers could be particularly beneficial considering antibiotic macrolides have immune-modulating properties that may be a mechanism responsible for improvement in this clinical sample (see [77]).

Another possible mechanism of the intervention is through the prokinetic qualities of erythromycin. Erythromycin is a macrolide that inhibits protein synthesis in specific bacteria [78] and can increase gastric motility [79]. Low doses of erythromycin have been used for its prokinetic qualities in patients with delayed gastric emptying [80]. The stimulation of oesophageal, gastric and small intestinal contractions are likely to partially explain commonly reported gastrointestinal side effects (i.e., diarrhoea, nausea, vomiting) of oral erythromycin (see [81]). Therefore, the prokinetic effect of erythromycin may be particularly beneficial for this sample when we consider that constipation is a common symptom for patients with comorbid IBS and/or small intestinal bacterial overgrowth (SIBO; [82]), and the prevalence of intestinal permeability in ME/CFS [20, 21]. Increased monitoring of gastrointestinal changes, SIBO and IBS symptoms would be useful in further studies.

Probiotics may also increase bowel transit [83] or have other modes of action. Possible mechanisms of probiotics include modulating inflammatory and immune responses through enhancing the epithelial barrier, adherence to the mucosal wall, direct (antimicrobial) or indirect (competitive exclusion) effects on pathogenic microbiota, and vagal signalling (see [33, 84,85,86]). Metabolic by-products from specific bacterial strains may also effect clinical presentations through the production of neurotransmitters (see [87]), short chain fatty acids through fermentation (see [33]), and cross-feeding, as discussed above. Advances in metabolomics methods would be useful to monitor functional changes during probiotic supplementation in ME/CFS patients.