Gut Microbiota Regulate Motor Deficits and Neuroinflammation in a Model of Parkinson’s Disease
Authors: Zehra Esra Ilhan
Collin Challis
Sandra Rocha
Pernilla Wittung-Stafshede
Stefan Janssen
Rob Knight
Ali Keshavarzian
Sarkis K Mazmanian
Catherine E Schretter
Kathleen M Shannon
Rosa Krajmalnik-Brown
Taren Thron
Justine W Debelius
Gauri G Shastri
Timothy R Sampson
Viviana Gradinaru
Marie-Francoise Chesselet
Journal: Cell (2016)
Discipline: MOLECULAR BIOLOGY & GENETICS
Keywords: Parkinson’s disease; gut-brain axis; microbiome; microglia; mouse model
Affiliations: Division of Biology & Biological Engineering, California Institute of Technology, Pasadena, CA 91125, USA. Electronic address: ., Department of Pediatrics, University of California, San Diego, San Diego, CA 92110, USA., Division of Biology & Biological Engineering, California Institute of Technology, Pasadena, CA 91125, USA., Swette Center for Environmental Biotechnology, Biodesign Institute, Arizona State University, Tempe, AZ 85287, USA., Biology and Biological Engineering Department, Chalmers University of Technology, Gothenburg 41296, Sweden., Department of Neurology, The David Geffen School of Medicine at UCLA, Los Angeles, CA 90095, USA., Department of Internal Medicine, Division of Gastroenterology, Rush University Medical Center, Chicago, IL 60612, USA., Department of Neurological Sciences, Section of Movement Disorders, Rush University Medical Center, Chicago, IL 60612, USA., Department of Pediatrics, University of California, San Diego, San Diego, CA 92110, USA; Department of Computer Science and Engineering, University of California, San Diego, San Diego, CA 92093, USA.

Abstract:  The intestinal microbiota influence neurodevelopment, modulate behavior, and contribute to neurological disorders. However, a functional link between gut bacteria and neurodegenerative diseases remains unexplored. Synucleinopathies are characterized by aggregation of the protein α-synuclein (αSyn), often resulting in motor dysfunction as exemplified by Parkinson's disease (PD). Using mice that overexpress αSyn, we report herein that gut microbiota are required for motor deficits, microglia activation, and αSyn pathology. Antibiotic treatment ameliorates, while microbial re-colonization promotes, pathophysiology in adult animals, suggesting that postnatal signaling between the gut and the brain modulates disease. Indeed, oral administration of specific microbial metabolites to germ-free mice promotes neuroinflammation and motor symptoms. Remarkably, colonization of αSyn-overexpressing mice with microbiota from PD-affected patients enhances physical impairments compared to microbiota transplants from healthy human donors. These findings reveal that gut bacteria regulate movement disorders in mice and suggest that alterations in the human microbiome represent a risk factor for PD. 

Retracted: No

PubPeer comments:
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 I have attempted to replicate the authors analysis on the basis of the data they have posted on dryad. Let s start with the motor performance data shown in Fig. 1A-D. The legend says that the data shown are representative of two experiments. The data posted (in the  MouseTreatmentMotorFunction.xlsx spreadsheet) does not identify those two experiments. However, examination of the  Hindlimb score column shows that only 5 animals were tested and their data correspond exactly to those shown in Fig. 1D. It would seem that those animals should correspond to the experiment shown. However, it is not possible to reproduce the other panels using the same animals. In fact, whether one takes that group, the complement or all animals, it is not possible to reproduce the values in the published panels. This can be seen, for example, by calculating the mean value for  Avg Adhesive Removal Time for the SPF ASO group (Fig. 1C second bar). For animals with a hindlimb score, the mean is 4.44, for animals without a hindlimb score, the mean is 11.92, while for all animals the mean is 8.18. None of these values corresponds to that in the Fig. 1C, which is close to 14. At best, the authors selected their representative data in Fig. 1 from the two experiments differently for different panels and are not prepared to identify how they did that. In any case, the sample sizes are so small that it is only worth testing the data pooling the two experiments. The authors published analysis contains two statistical errors: 1) they use parametric tests in a situation where the sample sizes are too small to verify the prerequisites (normality, homoscedasticity); 2) they fail to use a two-way test for the interaction between Treatment (SPF GF) and Genotype (WT ASO), which is what they actually need. Using a robust technique from Wilcox s WRS2 R package that is reported to offer good control of Type I errors (i.e. of false positives), we can show that only one of three motor tests has a significant interaction. ``` # Read data. The excel file must be in the same folder. library(gdata) mouse = read.xls( MouseTreatmentMotorFunction.xlsx , skip=3, header=TRUE, na.strings= nd ) m1 = droplevels(mouse[(mouse$Treatment== SPF ) | (mouse$Treatment== GF ),]) library(WRS2) med2way(m1$Avg.Beam.cross.time..sec. ~ m1$Treatment*m1$Genotype) ``` | | value |p.value| |----------------------|---------------:|---------------:| |m1$Treatment | 3.9219 | 0.0477| |m1$Genotype | 7.8725 | 0.0050| |m1$Treatment:m1$Genotype | 6.5400 | 0.0105| ``` med2way(m1$Avg.Pole.descent.time..sec. ~ m1$Treatment*m1$Genotype) ``` | | value |p.value| |----------------------|---------------:|---------------:| |m1$Treatment | 3.6945 | 0.0546| |m1$Genotype | 1.0006 | 0.3172| |m1$Treatment:m1$Genotype | 1.3757 | 0.2408| ``` med2way(m1$Avg.Adhesive.removal.time..sec. ~ m1$Treatment*m1$Genotype) ``` | | value |p.value| |----------------------|---------------:|---------------:| |m1$Treatment | 0.0016 | 0.9678| |m1$Genotype | 1.2529 | 0.2630| |m1$Treatment:m1$Genotype | 0.3522 | 0.5529| Thus, the authors conclusion that all three motor tests were affected doesn t replicate with a more robust analysis applied to their own data. I didn t consider it worth testing the Hindlimb score because the sample size was so small. Relevant experiments are also shown in Fig. 4. First, however, note that the data from the experiments illustrated in Fig. 1 appear to be recycled in this figure. Thus, Fig 4E is identical to Fig. 1D. Probably the pooled experiments are shown for the other motor measurements. The authors don t declare this reuse. This data contains somewhat larger samples in a complex and wasteful crossover experiment of colonising germ-free mice ( ExGF ) or treating SPF mice with antibiotics ( Abx ), before testing motor performance. Again, what is important here is the interaction in the two-way test (because they only test motor performance once in each group). As for the previous experiments, only one motor test out of three shows a significant interaction between genotype and final gut colonisation condition. The other data requested were the microglial diameters. This is supposedly supplied in the  SynucleinandInflammation.xlsx spreadsheet. Just like in the paper, the authors give no information about technical and biological replicates. Furthermore, they only supply diameter data for midbrain, data that is apparently not shown anywhere in the paper. It is therefore not possible to check whether the means and standard errors given in the paper reflect technical or biological replicates, although it seems likely that the authors mixed the two, which would be incorrect. In conclusion, despite the data access conditions at Cell, the authors are unable or unwilling to provide data enabling replication of a minimal set of the key results of their paper. The paper includes undeclared data recycling and unxeplained data selection. Parametric tests are applied incorrectly to small samples, while interaction effects are not tested when they should be. Technical replicates have probably been counted as biological replicates. Such statistical errors underlie the current crisis of unreproducible research. Researchers at CalTech and editors at Cell should know better, but clearly they do not. The limited reanalysis permitted by the data provided shows that the basic observations are weaker than reported. And the possible confounds of simple digestive problems remain. , 
 very relevant to this paper, on how the term  dysbiosis is used and misused in the literature: https: pubmed.ncbi.nlm.nih.gov 29018121 ,