Materials and methods

Luminal content samples were collected in operatory room before surgery from 24 colon cancer tissue specimens. After protein extraction and digestion, peptide mixtures were analyzed by high-resolution mass spectrometry. Bioinformatic analysis allowed peptide identification, label-free quantification and taxonomic/functional annotation. For each clinical variable, we identified the set of most discriminating peptides through a permutation-based sPLS regression approach. Significantly enriched taxa, functions and metabolic pathways were identified for each set of discriminating peptides, performing a sensitivity analysis considering covariate impact (age, sex and other clinical variables) and adjusting for multiple testing through a premutation-based approach.

3. Results

We identified 294, 94 and 568 microbial peptides discriminating for tumor stage, grade and TILs, respectively. Proteins produced by Bifidobacterium were found significantly enriched in high-stage tumors, whereas those expressed by Bacteroides spp. were over-represented in high-grade and TIL-negative tumor samples. Furthermore, microbial enzymes involved in tetrahydrofolate interconversion, glutamine biosynthesis and galactose catabolism were enriched in the colonic luminal metaproteome of high-stage/grade tumors.

4. Discussion and Conclusions

The metaproteomic approach used in this study has proven to be able to provide a detailed picture of the microbial and host components of the colonic luminal proteome. Moreover, promising correlations between the abundance of human and bacterial proteins and colon cancer clinicopathological features were found. Future studies with higher numbers of samples are needed to extend the investigation and confirm its biological value, as well as to validate their potential to enhance our knowledge concerning colorectal cancer progression.

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114 - Distinct gut microbiota and metabolome enterotypes associated with clinical phenotypes of Parkinson’s disease

1SARAH VASCELLARI, ¹VANESSA PALMAS, ¹ALESSANDRA SERRA, ¹FABRIZIO ANGIUS, ¹GIUSEPPINA SANNA, ¹VERONICA MADAU, ²MARIA LAURA SANTORU, ³MARTA MELIS, ⁴VALENTINA OPPO, ²LUIGI ATZORI, ⁴GIOVANNICOSSU, ¹ALDOMANZIN.

1Department of Biomedical Science, Microbiology and Virology Unit, University of Cagliari, Cagliari, Italy;

2Department of Biomedical Science, Pathology Unit, University of Cagliari, Cagliari, Italy;

3S.C. Neurology Unit, AOUCA, Cagliari, Italy;

4S.C. Neurology and Stroke Unit, AOBrotzu, Cagliari, Italy;

Abstract

Introduction: Parkinson’s disease (PD) is a clinically heterogeneous disorder characterized by distinct clinical phenotypesassociated to motor and non-motor dysfunctions. Most studies on motor deficits dichotomize PD into tremor dominant (TD) or non-tremor dominant (non-TD) phenotypes with akinetic-rigid features (AR). Different pathophysiological mechanisms may affect the onset of motor manifestations. Recent studies have suggested that gut microbes may be involved in PD pathogenesis and possibly impair motor function through microglial activation. The aim of this study was to investigate the gut microbiota and metabolome composition of PD patients in relation to TD and non-TD phenotypes.

Materials and Methods: Idiopathic PD patients (n = 56) were evaluated by the Movement Disorder Society-Unified Parkinson’s Disease part III and IV and by the Non-Motor Symptom Scale, and classified into two main groups according to subtypes categories. The gut microbiota and metabolome profiles of the PD patients were determined in fecal samples using 16S next generation sequencing and gas chromatography–mass spectrometry approaches.

Results: The results revealed that the overall gut microbiota structure significantly differs between TD and non-TD subtypes, showing a reduction in diversity and richness associated to non-TD phenotypes. In particular, we found a reduction in the relative abundance of protective bacteria (i.e., Lachnospiraceae, Blautia, Coprococcus, Lachnospira), and an increase of those correlated with pro-inflammatory activity (i.e., Enterobacteriaceae, Escherichia and Serratia) in association with the non-TD subtypes. Moreover, the levels of nicotinic acid, cadaverine, and glucuronic acid were altered in relation to the severity of non-tremor manifestations.

Discussion and Conclusions: Our study highlights that the gut microbiota of PD patients with TD and non-TD motor phenotypes differs in the bacterial diversity and taxonomic abundance, suggesting a possible relationship between gut dysbiosis and motor impairment. We hypothesize that the microbiota/metabolome enterotypes associated to non-TD subtypes may favor the development of a gut inflammatory milieu and gastrointestinal dysfunctions hence a more severe -synucleinopathy. This study adds further information on PD pathogenesis and emphasizes the potential pathophysiological correlation between the gut microbiota/metabolites and PD motor subtypes.

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Antonelli Alberto ... 96; 97; 125; 137 Antonelli Guido ... 60; 73; 86

Balestrieri Emanuela ... 40; 42; 48; 58 BALESTRIERI EMANUELA ... 122

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Castillo Pacheco Sergio Fernando ... 1; 15; 16; 23 Casuccio Alessandra ... 103

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Cirillo Daniela Maria ... 100

Cocuzza Clementina ... 124

codda Giulia... 115

Colao Maria Grazia ... 96; 97 Colicchio Roberta ... 10; 39; 69; 83; 118; 128 COLICCHIO ROBERTA ... 11

De Santis Federica ... 22; 100; 102 De Santis Riccardo ... 17

Della Rocca Maria Teresa ... 157; 190 Della Ventura Carla ... 111

DELL'ANNUNZIATA FEDERICA ... 167

DELL'AVERSANA CARMELA ... 167

Dellavia Claudia ... 200

Dell'Oste Valentina ... 1; 15; 16; 23 DELL'OSTE VALENTINA ... 3

Delogu Giovanni ... 20; 54; 109; 155 Dentali Francesco ... 89

Di Lodovico Silvia ... 24; 159; 214 Di Lorenzo Flaviana ... 83

193 Fanelli Marialaura ... 40; 42; 48; 58 FANELLI MARIALAURA ... 122 Fiorito Filomena ... 28; 112; 142; 186 Fiorito Giovanni ... 223

Franci Gianluigi ... 18; 31; 85; 170 FRANCI GIANLUIGI ... 167

194

Henrici De Angelis Lucia ... 100; 102 HEWELT-BELKA WERONIKA ... 3

195

Lucchesi Simone ... 107

Lucidi Vincenzina ... 100

Lunardelli Francesco ... 127

Lupetti Antonella ... 120; 132; 165; 220 Lupetti Veronica ... 175; 194

Matteucci Claudia ... 40; 42; 48; 58 MATTEUCCI CLAUDIA ... 122

Minutolo Antonella ... 40; 42; 48; 58 MINUTOLO ANTONELLA ... 122

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Nocera Francesca Paola ... 28; 112; 142; 186 Nostro Antonia ... 187; 217

Pereyra Boza Maria del Carmen ... 54

Perfetto Brunella ... 32

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Rossolini Gian Maria ... 96; 97; 125; 137 ROTARI EVDOCHIA... 153 Salustri Alessandro ... 20; 54; 109; 155 SALVATORE FRANCESCO ... 11

Salvatore Maria Michela ... 28

Salvatore Paola ... 10; 39; 69; 83; 118; 128 SALVATORE PAOLA ... 11

Sanfilippo Giuseppa... 103

Sanguinetti Maurizio ... 20; 54; 109; 155 Sanna Giuseppina ... 67; 218; 224

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Sinibaldi Vallebona Paola ... 40; 42; 48 sisto francesca ... 200

Stefani Stefania 133; 135; 145; 146; 202; 203; 222 STEFANI STEFANIA ... 77

Stefanizzi Valeria ... 46

Stelitano Debora ... 32; 85 Stornaiuolo Alessia ... 39

Stracquadanio Stefano ... 133; 135; 202; 203 Surico Giuseppe... 197

Vitiello Mariateresa ... 10; 39; 69; 83; 118; 128 VITIELLO MARIATERESA ... 11

199

WESSJOHANN LUDGER A. ... 67

Z Zagaglia Carlo ... 2; 50; 71 Zamagni Giulia ... 113

Zambito Ylenia ... 176

Zannella Carla ... 85

Zanotta Nunzia ... 9; 113 Zappalà Simona ... 135

Zara Francesca ... 178

Zarrilli Raffaele ... 183

ZARRILLI RAFFAELE ... 153

Zazzi Maurizio ... 98; 111 Zega Alessandra... 145

Zehender Gianguglielmo ... 111

Zingaropoli Maria Antonella ... 86

Ziparo Chiara ... 62

Zordan Marta ... 40; 42; 48 Zuccari Simone ... 62

Zuliani Giovanni ... 212