Investigation of the Relationship Between Akkermansia Genomic Diversity in Gut Microbiota and Parkinson’s Disease Dementia

Parkinson hastalığında (PH), genellikle sağlıkla ilişkilendirilen bir bakteri cinsi olan Akkermansia’nın bağırsak mikrobiyotasında artış gösterdiği bilinse de bu artışın nedeni tam olarak anlaşılamamıştır. Bu çalışmada Türkiye’deki PH hastalarında, bağırsak mikrobiyotasındaki muhtemel Akkermansia değişimlerinin belirlenmesi amaçlanmıştır. Bu amaçla, ilk kez shotgun metagenomik ve Akkermansia cinsine özgül bir yeni nesil dizileme (NGS) tekniği kullanılarak PH’de bilişsel bozukluk evreleriyle ilişkili olabilecek belirli Akkermansia suşlarının varlığı ve bu suşlarda bulunan potansiyel genler incelenmiştir. Bu kapsamda Türkiye’de toplanmış dört bağırsak mikrobiyotası örneği -üç demanslı PH (PHD) ve bir bilişsel bozukluğu olmayan sağlıklı kontrol (SK)- shotgun metagenomik dizileme yoluyla analiz edilmiş ve örneklerdeki Akkermansia cinsine ait genomlar yeniden inşa edilmiştir. Bu genomlar, veri tabanlarındaki Akkermansia cinsine ait genomlarla bir araya getirilerek özel bir veri tabanı oluşturulmuş ve Akkermansia cinsine özgül NGS uyumlu primerler bu veri tabanı kullanılarak tasarlanmıştır. Hedef gen bölgesinin çoğaltılması ve cins özgül yeni nesil dizileme için kütüphane hazırlama basamaklarının optimize edilmesinden sonra, 64 PH hastası [32 PHD ve 32 hafif bilişsel bozukluk gösteren PH (PH-MCI)] ile 26 SK’ye ait bağırsak mikrobiyotası örnekleri cins özgül amplikon dizileme ile analiz edilmiştir. Analizler sonucunda, bağırsak mikrobiyotası örneklerinde Akkermansia muciniphila türüne ait oldukları belirlenen yedi suşun varlığı tespit edilmiş ve iki suşun demanslı (PHD) ve demansı olmayan (PH-MCI, HC) gruplar arasındaki dağılımının anlamlı farklılık gösterdiği (p< 0.05) belirlenmiştir. Tespit edilen suşlara ait genomların gen içerikleri, karşılaştırmalı genomik analizler yoluyla incelediğinde yalnızca dağılımı demanslı ve demansı olmayan gruplar arasında anlamlı farklılık gösteren iki suşta bulunan 12 genin varlığı tahmin edilmiştir. Bu genlerin annotasyonları yapıldığında ise daha önce rapor edilmemiş ve işlevi bilinmeyen genler oldukları görülmüştür. Bu çalışmada, ilk kez Türkiye’de toplanmış PH hastalarına ait bağırsak mikrobiyotası örneklerinin shotgun metagenomik analizleri gerçekleştirilmiş, özel olarak Akkermansia cinsinin analizi için cins-özgül bir amplikon dizileme yöntemi geliştirilmiş ve bu yöntem kullanılarak PH’de bilişsel bozukluk evreleriyle ile ilişkili olabilecek Akkermansia suşları ve genleri tespit edilmiştir. Elde edilen sonuçlar, tür ya da suş düzeyindeki farklılıkların araştırılmasının, bağırsak mikrobiyotasındaki PH ile ilişkili değişimlerin daha iyi anlaşılmasına yardımcı olabileceğine işaret etmektedir.Although it is known that the relative abundance of Akkermansia, a bacterial genus commonly associated with health, increases in the gut microbiota of Parkinson’s disease (PD) patients, the exact reason for this increase remains unclear. This study was aimed to identify potential changes in Akkermansia within the gut microbiota of PD patients in Türkiye. For this purpose, shotgun metagenomics and a novel Akkermansia genus-specific amplicon sequencing technique was used to investigate the presence of specific Akkermansia strains associated with cognitive impairment (CI) stages in PD and to examine potential genes within these strains. In this context, four gut microbiota samples from Türkiye -three PD with dementia (PDD) and one healthy control without CI (HC)- were analyzed by shotgun metagenomics and metagenome-assembled genomes assigned to Akkermansia genus were reconstructed. Then, a custom database was created by combining these genomes with the Akkermansia genomes in public databases and next generation sequencing (NGS) compatible primers specific to the genus Akkermansia were designed using this database. After optimization of amplification and library preparation steps for genus-specific next generation sequencing, gut microbiota samples from 64 PD patients [32 PDD and 32 PD with mild CI (PD-MCI)] and 26 HCs were analyzed by genus-specific amplicon sequencing. The results revealed the presence of seven strains assigned to Akkermansia muciniphila in gut microbiota samples, two of which showed significant distribution differences (p< 0.05) between demented (PDD) and non-demented groups (PD-MCI, HC). When gene contents of the detected Akkermansia genomes were examined through comparative genomic analysis, the presence of 12 genes only in Akkermansia genomes specific to non-demented groups were predicted. The annotations of these genes showed that they were not reported before with unknown functions. In this study, for the first time, gut microbiota samples from PD patients in Türkiye were analyzed using shotgun metagenomics, a novel genus-specific amplicon sequencing method was developed specifically for the analysis of Akkermansia genus, and then Akkermansia strains and genes potentially associated with CI stages in PD were identified using this method. The results underscore that investigating the species or strain level differences could help better understanding of the changes associated with PD in the human gut microbiota

Metaproteogenomic analysis of saliva samples from Parkinson's disease patients with cognitive impairment

Cognitive impairment (CI) is very common in patients with Parkinson's Disease (PD) and progressively develops on a spectrum from mild cognitive impairment (PD-MCI) to full dementia (PDD). Identification of PD patients at risk of developing cognitive decline, therefore, is unmet need in the clinic to manage the disease. Previous studies reported that oral microbiota of PD patients was altered even at early stages and poor oral hygiene is associated with dementia. However, data from single modalities are often unable to explain complex chronic diseases in the brain and cannot reliably predict the risk of disease progression. Here, we performed integrative metaproteogenomic characterization of salivary microbiota and tested the hypothesis that biological molecules of saliva and saliva microbiota dynamically shift in association with the progression of cognitive decline and harbor discriminatory key signatures across the spectrum of CI in PD. We recruited a cohort of 115 participants in a multi-center study and employed multi-omics factor analysis (MOFA) to integrate amplicon sequencing and metaproteomic analysis to identify signature taxa and proteins in saliva. Our baseline analyses revealed contrasting interplay between the genus Neisseria and Lactobacillus and Ligilactobacillus genera across the spectrum of CI. The group specific signature profiles enabled us to identify bacterial genera and protein groups associated with CI stages in PD. Our study describes compositional dynamics of saliva across the spectrum of CI in PD and paves the way for developing non-invasive biomarker strategies to predict the risk of CI progression in PD.FEMS Research and Training Gran

Investigation of the Effect of Acamprosate Treatment on Heart Contractions in Alcohol-Dependent Rats

Background/ Aim: Chronic alcohol use leads to impaired heart contraction and also causes a direct toxic effect on myocardial function. Acamprosate, which is widely used in alcohol dependence, is not known to have a pharmacological effect on cardiac contraction. Therefore, this study aimed to investigate the effects of acamprosate on the heart muscle. Materials and Methods: A total of 32 female Wistar rats were divided four groups as control (10 mg/kg/g saline) group, alcohol (10 mg/kg/g alcohol + 10 mg/kg/g saline) group, acamprosate (200 mg/kg/g) group and alcohol+ acamprosate groups (10 mg/kg/g alcohol + 200 mg/kg/g acamprosate + 10 mg/kg/g saline). Alcoholic rats were scored for alcohol dependence and withdrawal. After that, the rats were sacrificed, respectively and the heart tissue was removed. The amplitude and contraction frequencies of the atrium tissue taken from the heart tissue were measured in the isolated tissue bath. Results: Alcohol dependence and withdrawal symptoms were observed in the Alcohol group and Alcohol+Acamprosate group (

Creutzfeldt-Jacob Disease: Two Case Reports

Creutzfeldt-Jakob Disease (CJD) is characterised by subacute progressive dementia, cerebellar ataxia, myoclonic jerks together with pyramidal and extrapyramidal signs. It is a rare prion disease and definitive diagnosis can only be made by biopsy. It becomes progressively worse and the death is the rule. We presented two CJD cases because of their demonstrative characteristics. A 43 year-old female and a 52 year-old male patient was suspected to be CJD due to presence of subacute severe cognitive deterioration, neuropsychiatric disturbances, myoclonic jerks, ataxia, pyramidal and extrapyramidal signs and also periodic spike and wave complexes in EEG. Patients were lost in a short period of time because of the complications of disease process. Medical autopsy were done in both cases for definitive diagnosis and autopsy results displayed characteristic pathologic findings of CJD. Patients were diagnosed as definitive sporadic CJD according to Master’s, French and European criterias. CJD should be considered in patients with rapidly progressive dementia, that starts with various neuropsychiatric symptoms. Although seen very rare, CJD is a untreatable, fatal disease. Therefore we emphasize that, preventive precaution should be taken when a CJD diagnosis is suspecte

1938-1960 yılları arasında TMO’nun tarihi

Ankara : İhsan Doğramacı Bilkent Üniversitesi İktisadi, İdari ve Sosyal Bilimler Fakültesi, Tarih Bölümü, 2016.This work is a student project of the The Department of History, Faculty of Economics, Administrative and Social Sciences, İhsan Doğramacı Bilkent University.by Emiroğlu, Kudret

Axillary microbiota is associated with cognitive impairment in parkinson's disease patients

Cognitive impairment (CI) is among the most common non-motor symptoms of Parkinson's disease (PD), with a substantially negative impact on patient management and outcome. The development and progression of CI exhibits high interindividual variability, which requires better diagnostic and monitoring strategies. PD patients often display sweating disorders resulting from autonomic dysfunction, which has been associated with CI. Because the axillary microbiota is known to change with humidity level and sweat composition, we hypothesized that the axillary microbiota of PD patients shifts in association with CI progression, and thus can be used as a proxy for classification of CI stages in PD. We compared the axillary microbiota compositions of 103 PD patients (55 PD patients with dementia [PDD] and 48 PD patients with mild cognitive impairment [PD-MCI]) and 26 cognitively normal healthy controls (HC). We found that axillary microbiota profiles differentiate HC, PD-MCI, and PDD groups based on differential ranking analysis, and detected an increasing trend in the log ratio of Corynebacterium to Anaerococcus in progression from HC to PDD. In addition, phylogenetic factorization revealed that the depletion of the Anaerococcus, Peptoniphilus, and W5053 genera is associated with PD-MCI and PDD. Moreover, functional predictions suggested significant increases in myo-inositol degradation, ergothioneine biosynthesis, propionate biosynthesis, menaquinone biosynthesis, and the proportion of aerobic bacteria and biofilm formation capacity, in parallel to increasing CI. Our results suggest that alterations in axillary microbiota are associated with CI in PD. Thus, axillary microbiota has the potential to be exploited as a noninvasive tool in the development of novel strategies.Suleyman Yildirim from the Scientific and Technological Research Council of Turkey (TUBITAK

Metaproteogenomic analysis of saliva samples from Parkinson's disease patients with cognitive impairment

Cognitive impairment (CI) is very common in patients with Parkinson's Disease (PD) and progressively develops on a spectrum from mild cognitive impairment (PD-MCI) to full dementia (PDD). Identification of PD patients at risk of developing cognitive decline, therefore, is unmet need in the clinic to manage the disease. Previous studies reported that oral microbiota of PD patients was altered even at early stages and poor oral hygiene is associated with dementia. However, data from single modalities are often unable to explain complex chronic diseases in the brain and cannot reliably predict the risk of disease progression. Here, we performed integrative metaproteogenomic characterization of salivary microbiota and tested the hypothesis that biological molecules of saliva and saliva microbiota dynamically shift in association with the progression of cognitive decline and harbor discriminatory key signatures across the spectrum of CI in PD. We recruited a cohort of 115 participants in a multi-center study and employed multi-omics factor analysis (MOFA) to integrate amplicon sequencing and metaproteomic analysis to identify signature taxa and proteins in saliva. Our baseline analyses revealed contrasting interplay between the genus Neisseria and Lactobacillus and Ligilactobacillus genera across the spectrum of CI. The group specific signature profiles enabled us to identify bacterial genera and protein groups associated with CI stages in PD. Our study describes compositional dynamics of saliva across the spectrum of CI in PD and paves the way for developing non-invasive biomarker strategies to predict the risk of CI progression in PD

Automatic transcription of Ottoman documents using deep learning

With the accelerated pace of digitization, a vast collection of Ottoman documents has become accessible to researchers and the general public. However, most users interested in these documents are unable to read them, as the text is Turkish written in the Arabic-Persian script. Manual transcription of such a massive amount of documents is also beyond the capacity of human experts. With the advancements in deep learning, we have been able to provide a solution to the long-standing problem of automatic transcription of printed Ottoman documents. We evaluated three decoding strategies including Word Beam Search that allows to use a recognition lexicon and n-gram statistics during the decoding phase. Furthermore, the effect of lexicon size and coverage and language modelling via character or word n-grams are also evaluated. Using a general purpose large lexicon of the Ottoman era (260K words and 86% test coverage), the performance is measured as 6.59% character error rate and 28.46% word error rate on a test set of 6, 828 text lines

Improved Pt/C electrocatalysts for methanol oxidation prepared by different reducing agents and surfactants and DFT studies on it

In this work, PtCl4 as precursor; sodium borohydride (Cat I), hydrazinium hydroxide (Cat II), and formaldehyde (Cat III) as reducing agents; and 1-heptanamine (a), N-methyl-1-heptanamine (b), and N, N-dimethyl-1-heptanamine (c) as surfactants were used to prepare platinum nanoparticles which were then dispersed on carbon XC-72 for use as catalysts in the methanol oxidation reaction. XRD and TEM results indicate that the platinum has a face-centered cubic structure and is found as small and agglomerated particles in different shapes, sizes, and densities. Cat I comprises small (similar to 5 nm) cubic and formless agglomerated (similar to 20-similar to 300 nm) particles, Cat II is composed of small (similar to 5 nm) and a significant number of quite dense spherical agglomerated (similar to 20-similar to 150 nm) particles, and Cat III contains large number of small (similar to 5 nm) and a small number of spherical, less dense, and agglomerated (similar to 20-similar to 200 nm) particles. XPS data shows that the platinum exists in two different oxidation states Pt(0) (similar to 64.5-similar to 69.6%) and Pt(IV) (similar to 35.5-similar to 30.4%), and platinum surface also contains OH, H2O, C-O, C=O, and carbon. DFT and FTIR show that the surfactants decompose to form partially crystalline carbon. Electrochemical studies reveal that performance order of the catalysts towards the methanol oxidation reaction is Cat II < Cat I < Cat III, and that Cat IIIc has the highest performance, which is 2.23 times larger than E-TEK catalysts. It was found that the performance of the catalysts depends on the kind of surfactant, reducing agent, electrochemical surface area, percent platinum utility, roughness factor, and If/(I)r ratio