Table 2.

Studies investigating the ALS microbiome. Includes non-gut microbiome studies not described further in the main text

Study	Numbers and phenotypes	Intervention/ Hypothesis generating	Sample	Methodology	Outcomes
Alonso, R. et al. 2015 [39]	5 ALS and 3 controls (CSF sample analysis), 6 ALS and 4 controls (brain samples)	Hypothesis generating	CSF, brain tissue	PCR, immunohistochemistry and proteomics	Evidence of fungal infection both in CSF and brain tissue of ALS patients. Evidence of some fungal presence also in controls.
Fang, X., et al. 2016 [29]	6 ALS patients, 5 healthy controls	Hypothesis generating	Faecal	16S microbe identification method on extracted DNA	In ALS group (compared to control): Decreased Firmicutes/Bacteroidetes ratio Significantly increased Dorea genus Significantly reduced Oscillibacter, Anaerostipes, Lachnospiraceae
Rowin, J., et al. 2017 [30]	5 patients, 4 definite ALS, one Brachial Amyotrophic Diplegia vs control reference ranges (n = 96)	Hypothesis generating	Faecal	16S microbe identification method on extracted DNA	Decreased diversity in disease group compared to healthy reference. Low Firmicutes/Bacteroidetes ratio in 3 of 4 ALS patients.
Brenner, D., et al. 2018 [32]	25 ALS patients with 32 age- and gender-matched healthy controls	Hypothesis generating	Faecal	16S microbe identification method on extracted DNA, predicted metagenomes	Only 1 genus found statistically different, Ruminococcaceae, out of 336 considered and non-significant higher diversity in ALS group.
Zhai, C.D., et al. 2019 [31]	8 ALS patients, 8 healthy controls	Hypothesis generating	Faecal	16S microbe identification method on extracted DNA, evaluation of metabolite concentrations by spectrophotometry (SCFAs, NO2-N/NO3-N, GABA)	Report the following trends but no mention of significance: Firmicutes/Bacteroidetes ratio increased in ALS group. Methanobrevibacter increased, Faecalibacterium and Bacteroides decreased in ALS patients. Small differences in average metabolite concentrations of ALS and control groups reported.
Sun, J., et al. 2019 [37]	2484 ALS and 12,420 age-matched and sex-matched controls.	Hypothesis generating	Medical records	Nested case–control study using several Swedish national registers. Conditional logistic regression model.	Antibiotic use found to be associated with higher risk of ALS. Findings irrespective of reason for antibiotic administration (respiratory, urinary tract and soft tissue infections)
Alonso, R. et al. 2019 [38]	11 ALS tissue samples from brain and spinal cord, control data appears to be from a previous study (data from 9 individuals used in a PCA).	Hypothesis generating	Brain and spinal cord tissues	PCR, next generation sequencing and immunohistochemistry	All methods employed showed evidence of bacteria present in brain and spinal cord tissue of ALS patients.
Blacher, E., et al. 2019 [17]	37 ALS patients, 29 healthy controls.	Hypothesis generating	Faecal	Shotgun metagenomic sequencing. Metabolomics of blood serum.	Microbiome composition of ALS group significantly different to control group. Groups significantly different in global bacterial gene content with ALS group deficient in several genes associated with metabolism of tryptophan and nicotinamide. Various metabolites differentially expressed in ALS sera compared to controls, including metabolites of the tryptophan-nicotinamide pathway. Proposed link between bacteria-derived nicotinamide and protection from ALS.
Di Gioia, D., et al. 2020 [33]	50 ALS, 50 healthy age/sex-matched controls	Both	Faecal	16S microbe identification method on extracted DNA. Quantitative PCR for selected microbes. Preliminary comparison of disease vs control samples using PCR-DGGE. Treatment (6 month) with Lactobacillus fermentum, Lactobacillus delbrueckii, Lactobacillus plantarum, Lactobacillus salivarius.	Levels of various microbial genera found to be significantly increased/decreased in abundance in ALS samples compared to healthy controls. Significant decrease in OTU number in probiotic trial longitudinal samples i.e. richness of gut microbiota declines as disease progresses. Probiotic treatment did alter gut microbiota, but without moving biodiversity towards that seen in controls. No impact on disease progression observed in probiotic-treated group.
Ngo, S.T., et al. 2020 [34]	49 probable/ definite ALS, 51 healthy controls	Hypothesis generating	Faecal	16S microbe identification method on extracted DNA. Taxa comparison. Predictive metagenomic analyses.	Overall no difference between faecal microbiomes of ALS patients and healthy controls. However, a subset (four) of ALS samples showed differences in beta-diversity. Higher species diversity associated with faster disease progression. Increased F:B ratio also linked to accelerated decline. Considered other clinical, metabolic and anthropometric features and none correlated with microbiome.
Zeng, Q., et al. 2020 [35]	20 probable/definite ALS, 20 healthy controls	Hypothesis generating	Faecal	16S microbe identification method on extracted DNA. Shotgun metagenomic sequencing on 10 ALS and 10 control samples. Metabolomic analysis (all 40 samples).	Reduced F:B ratio in ALS samples compared to controls. Evidence of higher OTU diversity and some change in structure of intestinal microbiota community in ALS samples. Decreased function of various metabolic pathways inferred from sequencing data, backed up to a degree by the metabolic data.