Impact of Refined and Unrefined Sugar and Starch on the Microbiota in Dental Biofilm.

Aims and Objective: Sugar is not only associated with dental diseases but also, along with carbohydrates, is linked to various health issues including obesity, cancer, diabetes, heart, liver, and kidney-related diseases. At the same time, a polyphenol present in unrefined sugar and starch (UReSS) is shown to inhibit microbial growth and prevent biofilms and dental plaque. The question arises, "is sugar the causative agent for dental diseases, or is its refined form the cause?" The objective of this study is to conduct in-vivo studies of the impact of refined and unrefined sugar and starch on the microbiota of dental biofilm. Materials and Methods: An in-vivo study was performed using saliva and dental biofilm samples collected from 75 healthy subjects. For this study, healthy volunteers (n = 75) were randomly divided into five groups and were given sweet meals either made with refined white sugar and white rice (ReSS) or with unrefined brown sugar and red rice (UReSS). This was followed by using or not using a polyphenolic mouthwash. Before and after 4 h of eating a sweet meal, the saliva and dental plaque were collected and the DNA was analyzed by 16s metagenomic sequencing. The results were expressed in fold change of bacteria from 0 to 4 h. Statistical analyses have been performed by logarithmic linear discriminant analysis (LDA), Student's t-test, and Wilcoxon signed-rank test. Results: Upon LEfSe and statistical analysis, in-vivo experiments clearly showed that UReSS significantly decreased bacteria associated with dental diseases. In contrast, ReSS showed a significant increase in Actinomyces, Streptococcus, and Selenomonas with a high LDA score (Log 4.2) and statistical significance (P < 0.003). Mouthwash significantly decreased bacterial taxa associated with diseases in both the ReSS and UReSS groups. The in-vivo study showed a significant increase and decrease in Streptococcus levels in refined and unrefined sugar groups, respectively. Conclusion: In conclusion, polyphenols aid in the prevention of dental caries. This study recommends using polyphenol-rich unrefined sugars and carbohydrates for both oral and general health. This study is the first of its kind to bring awareness to the effects of refined and unrefined starch and sugars on the oral microbiota.

Spinal fluid IgG antibodies from patients with demyelinating diseases bind multiple sclerosis-associated bacteria.

A panel of 10 IgG enzyme-linked immunosorbent assays (ELISAs) were developed for the detection of anti-microbial immune responses in the cerebrospinal fluid (CSF) of patients with demyelinating diseases (DD). The anti-microbial ELISA assays follow on prior human brain tissue RNA sequencing studies that established multiple sclerosis (MS) microbial candidates. Lysates included in the ELISA panel were derived from Akkermansia muciniphila, Atopobium vaginae, Bacteroides fragilis, Lactobacillus paracasei, Odoribacter splanchnicus, Pseudomonas aeruginosa, Cutibacterium (Propionibacterium) acnes, Fusobacterium necrophorum, Porphyromonas gingivalis, and Streptococcus mutans. CSF responses from patients with demyelinating diseases (DD, N = 14) were compared to those with other neurological diseases (OND, N = 8) and controls (N = 13). Commercial positive and negative control CSF specimens were run with each assay. ELISA index values were derived for each specimen against each of the 10 bacterial lysates. CSF reactivity was significantly higher in the DD group compared to the controls against Akkermansia, Atopobium, Bacteroides, Lactobacillus, Odoribacter, and Fusobacterium. Four of the 11 tested DD group subjects had elevated antibody indexes against at least one of the 10 bacterial species, suggesting intrathecal antibody production. This CSF serological study supports the hypothesis that several of the previously identified MS candidate microbes contribute to demyelination in some patients. KEY MESSAGES: A panel of 10 IgG enzyme-linked immunosorbent assays (ELISAs) were developed for the detection of anti-microbial immune responses in the cerebrospinal fluid (CSF) of patients with demyelinating diseases, including multiple sclerosis and acute disseminated encephalomyelitis. CSF reactivity was significantly higher in the demyelination group compared to the controls against the bacteria Akkermansia, Atopobium, Bacteroides, Lactobacillus, Odoribacter, and Fusobacterium. Several of the demyelination subjects had elevated antibody indexes against at least one of the 10 antigens, suggesting at least limited intrathecal production of anti-bacterial antibodies. This CSF serological study supports the hypothesis that several of the previously identified MS candidate microbes contribute to demyelination in some patients.

A Novel, Simple, Frequent Oral Cleaning Method Reduces Damaging Bacteria in the Dental Microbiota.

AIM: Dental diseases can be prevented by reducing early bacterial colonization in biofilm, a precursor to mature dental plaque. Most studies on dental disease pathogenesis focus on mature plaque and fail to address the impact of oral cleaning on biofilm formation. Here we used next-generation metagenomics to assess the effects of a new method of regular, simple biofilm disruption on the oral metagenome. MATERIALS AND METHODS: This was a randomized, controlled study of 45 healthy children divided into three groups. Participants avoided oral cleaning for 3 days and then performed 10 days of oral cleaning either by: (1) brushing and tongue cleaning twice a day (BT) with toothpaste; (2) Gum and tooth rubbing with Index Finger Tongue cleaning and water Swishing (GIFTS) after each meal, snack, and drink; or (3) GIFTS twice a day with nano-charcoal and tongue cleaning (CT) (n = 15 per group). Saliva, plaque, and tongue scraping samples were collected on day 0 and 10 for quantitative polymerase chain reaction (qPCR) and next-generation metagenomics sequencing to analyze microbiome taxa differences between groups. RESULTS: GIFTS more significantly reduced (P < 0.004) total bacteria in saliva than BT (P < 0.02). Metagenomics revealed a significant reduction in Firmicutes in GIFTS and CT tongue samples compared to BT samples. BT and CT saliva samples showed significantly more Streptococcus species than GIFTS saliva samples. In the plaque samples, GIFTS cleaning significantly reduced early colonizers, including Streptococcus, compared to the BT and CT methods. CONCLUSION: Here, we introduce the "frequent disruption of biofilm" concept for enhanced oral hygiene. GIFTS can be used to prevent early bacterial colonization of biofilm and plaque formation in both small children and adults. Frequent biofilm disturbance more effectively disrupts early bacterial colonization than twice oral cleaning, is nonabrasive, and is, therefore, a practical and straightforward complement to regular toothbrushing for improved oral hygiene and disease prevention.

Spectrum of Microbial Sequences and a Bacterial Cell Wall Antigen in Primary Demyelination Brain Specimens Obtained from Living Patients.

Multiple sclerosis (MS) is an autoimmune disease characterized by multiple lesions in the brain and spinal cord. We used RNA sequencing to identify microbial sequences and characterize human gene expression patterns in 30 human brain biopsy specimens. RNAs which aligned to known microbial taxa, were significantly enriched in 10 of 12 primary demyelination (MS) brain specimens compared to a group of 15 epilepsy controls, leading to a list of 29 MS microbial candidate genera from 11 different phyla. Most of the candidate MS microbes are anaerobic bacteria. While there were some shared candidates, each of the 10 MS samples with significant microbial RNA enrichment had a distinct set microbial candidates. The fraction of microbial sequencing reads was greater for the MS group (128.8 PPM) compared to the controls (77.4 PPM, p = 0.016). Bacterial peptidoglycan was demonstrated in brain tissue sections from several MS subjects. Human gene expression analysis showed increased expression of inflammation-related pathways in the MS group. This data shows that demyelinating brain lesions are associated with the presence of microbial RNA sequences and bacterial antigen. This suggests that MS is triggered by the presence of a diverse set of microbes within a lesion.

Deep sequencing to identify the causes of viral encephalitis.

Deep sequencing allows for a rapid, accurate characterization of microbial DNA and RNA sequences in many types of samples. Deep sequencing (also called next generation sequencing or NGS) is being developed to assist with the diagnosis of a wide variety of infectious diseases. In this study, seven frozen brain samples from deceased subjects with recent encephalitis were investigated. RNA from each sample was extracted, randomly reverse transcribed and sequenced. The sequence analysis was performed in a blinded fashion and confirmed with pathogen-specific PCR. This analysis successfully identified measles virus sequences in two brain samples and herpes simplex virus type-1 sequences in three brain samples. No pathogen was identified in the other two brain specimens. These results were concordant with pathogen-specific PCR and partially concordant with prior neuropathological examinations, demonstrating that deep sequencing can accurately identify viral infections in frozen brain tissue.

Profiling viral infections in grapevine using a randomly primed reverse transcription-polymerase chain reaction/macroarray multiplex platform.

Crop-specific diagnostics to simultaneously detect a large number of pathogens provides an invaluable platform for the screening of vegetative material prior to its propagation. Here we report the use of what is to-date the largest published example of a crop-specific macroarray for the detection of 38 of the most prevalent or emergent viruses to infect grapevine. The reusable array consists of 1,578 virus-specific 60 to 70mer oligonucleotide probes and 19 plant and internal control probes spotted onto an 18 × 7 cm nylon membrane. In a survey of 99 grapevines from the United States and Europe, virus infections were detected in 46 selections of Vitis vinifera, V. labrusca, and interspecific hybrids. The majority of infected vines (30) was singly infected, while 16 were mixed-infected with viruses from two or more families. Representatives of the four main virus families Betaflexiviridae, Closteroviridae, Secoviridae, and Tymoviridae present in grapevines were found alone and in combination, with a notable bias in representation by members of the family Tymoviridae. This work demonstrates the utility of the macroarray platform for the multiplex detection of viruses in a single crop, its potential for characterizing grapevine virus associations, and usefulness for rapid diagnostics of introduced material in quarantine centers or in certification programs.

Sustained interactions between T cell receptors and antigens promote the differentiation of CD4⁺ memory T cells.

During CD4⁺ T cell activation, T cell receptor (TCR) signals impact T cell fate, including recruitment, expansion, differentiation, trafficking, and survival. To determine the impact of TCR signals on the fate decision of activated CD4⁺ T cells to become end-stage effector or long-lived memory T helper 1 (Th1) cells, we devised a deep-sequencing-based approach that allowed us to track the evolution of TCR repertoires after acute infection. The transition of effector Th1 cells into the memory pool was associated with a significant decrease in repertoire diversity, and the major histocompatibility complex (MHC) class II tetramer off rate, but not tetramer avidity, was a key predictive factor in the representation of individual clonal T cell populations at the memory stage. We conclude that stable and sustained interactions with antigens during the development of Th1 responses to acute infection are a determinative factor in promoting the differentiation of Th1 memory cells.

Combining quantitative genetic footprinting and trait enrichment analysis to identify fitness determinants of a bacterial pathogen.

Strains of Extraintestinal Pathogenic Escherichia c oli (ExPEC) exhibit an array of virulence strategies and are a major cause of urinary tract infections, sepsis and meningitis. Efforts to understand ExPEC pathogenesis are challenged by the high degree of genetic and phenotypic variation that exists among isolates. Determining which virulence traits are widespread and which are strain-specific will greatly benefit the design of more effective therapies. Towards this goal, we utilized a quantitative genetic footprinting technique known as transposon insertion sequencing (Tn-seq) in conjunction with comparative pathogenomics to functionally dissect the genetic repertoire of a reference ExPEC isolate. Using Tn-seq and high-throughput zebrafish infection models, we tracked changes in the abundance of ExPEC variants within saturated transposon mutant libraries following selection within distinct host niches. Nine hundred and seventy bacterial genes (18% of the genome) were found to promote pathogen fitness in either a niche-dependent or independent manner. To identify genes with the highest therapeutic and diagnostic potential, a novel Trait Enrichment Analysis (TEA) algorithm was developed to ascertain the phylogenetic distribution of candidate genes. TEA revealed that a significant portion of the 970 genes identified by Tn-seq have homologues more often contained within the genomes of ExPEC and other known pathogens, which, as suggested by the first axiom of molecular Koch's postulates, is considered to be a key feature of true virulence determinants. Three of these Tn-seq-derived pathogen-associated genes--a transcriptional repressor, a putative metalloendopeptidase toxin and a hypothetical DNA binding protein--were deleted and shown to independently affect ExPEC fitness in zebrafish and mouse models of infection. Together, the approaches and observations reported herein provide a resource for future pathogenomics-based research and highlight the diversity of factors required by a single ExPEC isolate to survive within varying host environments.

Macroarray detection of grapevine leafroll-associated viruses.

Grapevine leafroll-associated viruses (GLRaVs) are an emerging group of viruses that represent a significant threat to the global productivity and sustainability of the grapevine industry. Their control is achieved through the identification and elimination of infected vines, and the use of planting material derived from virus-tested, certified stocks. As such, much effort has been invested in developing reliable molecular diagnostic techniques. In this work, we report the development of a macroarray assay for the detection of the principal GLRaVs. In total 314 70-mer oligonucleotides specific to GLRaV-1, -2, -3, -4, -7, and GLRaV-4 strains 5, 6, 9 and Pr were spotted onto a 11×7cm nylon membrane. Thirty-four grapevine samples from various origins were tested by the macroarray, RT-PCR and ELISA. Thirty were positive for virus infection using RT-PCR, 28 by ELISA and 25 by the macroarray. Mixed infections were identified by macroarray in two samples and confirmed by RT-PCR or ELISA. There were a few discrepancies between methods that were most likely due to differences in the sensitivity of detection, and in the case of the macroarray, limitations in the sequence data available for certain virus species in the design of the oligonucleotides. This work demonstrates the successful application of macroarray methodology using randomly primed and sequence-nonspecific amplified cDNAs derived from grapevine total RNA extracts, and provides a proof-of-principal for unbiased multiplex detection using a single robust platform.

Deep sequencing for the detection of virus-like sequences in the brains of patients with multiple sclerosis: detection of GBV-C in human brain.

Multiple sclerosis (MS) is a demyelinating disease of unknown origin that affects the central nervous system of an estimated 400,000 Americans. GBV-C or hepatitis G is a flavivirus that is found in the serum of 1-2% of blood donors. It was originally associated with hepatitis, but is now believed to be a relatively non-pathogenic lymphotropic virus. Fifty frozen specimens from the brains of deceased persons affected by MS were obtained along with 15 normal control brain specimens. RNA was extracted and ribosomal RNAs were depleted before sequencing on the Illumina GAII. These 36 bp reads were compared with a non-redundant database derived from the 600,000+ viral sequences in GenBank organized into 4080 taxa. An individual read successfully aligned to the viral database was considered to be a "hit". Normalized MS specimen hit rates for each viral taxon were compared to the distribution of hits in the normal controls. Seventeen MS and 11 control brain extracts were sequenced, yielding 4-10 million sequences ("reads") each. Over-representation of sequence from at least one of 12 viral taxa was observed in 7 of the 17 MS samples. Sequences resembling other viruses previously implicated in the pathogenesis of MS were not significantly enriched in any of the diseased brain specimens. Sequences from GB virus C (GBV-C), a flavivirus not previously isolated from brain, were enriched in one of the MS samples. GBV-C in this brain specimen was confirmed by specific amplification in this single MS brain specimen, but not in the 30 other MS brain samples available. The entire 9.4 kb sequence of this GBV-C isolate is reported here. This study shows the feasibility of deep sequencing for the detection of occult viral infections in the brains of deceased persons with MS. The first isolation of GBV-C from human brain is reported here.

VIPR: A probabilistic algorithm for analysis of microbial detection microarrays.

BACKGROUND: All infectious disease oriented clinical diagnostic assays in use today focus on detecting the presence of a single, well defined target agent or a set of agents. In recent years, microarray-based diagnostics have been developed that greatly facilitate the highly parallel detection of multiple microbes that may be present in a given clinical specimen. While several algorithms have been described for interpretation of diagnostic microarrays, none of the existing approaches is capable of incorporating training data generated from positive control samples to improve performance. RESULTS: To specifically address this issue we have developed a novel interpretive algorithm, VIPR (Viral Identification using a PRobabilistic algorithm), which uses Bayesian inference to capitalize on empirical training data to optimize detection sensitivity. To illustrate this approach, we have focused on the detection of viruses that cause hemorrhagic fever (HF) using a custom HF-virus microarray. VIPR was used to analyze 110 empirical microarray hybridizations generated from 33 distinct virus species. An accuracy of 94% was achieved as measured by leave-one-out cross validation. CONCLUSIONS: VIPR outperformed previously described algorithms for this dataset. The VIPR algorithm has potential to be broadly applicable to clinical diagnostic settings, wherein positive controls are typically readily available for generation of training data.

An enhanced single base extension technique for the analysis of complex viral populations.

Many techniques for the study of complex populations provide either specific information on a small number of variants or general information on the entire population. Here we describe a powerful new technique for elucidating mutation frequencies at each genomic position in a complex population. This single base extension (SBE) based microarray platform was designed and optimized using poliovirus as the target genotype, but can be easily adapted to assay populations derived from any organism. The sensitivity of the method was demonstrated by accurate and consistent readouts from a controlled population of mutant genotypes. We subsequently deployed the technique to investigate the effects of the nucleotide analog ribavirin on a typical poliovirus population through two rounds of passage. Our results show that this economical platform can be used to investigate dynamic changes occurring at frequencies below 1% within a complex nucleic acid population. Given that many key aspects of the study and treatment of disease are intimately linked to population-level genomic diversity, our SBE-based technique provides a scalable and cost-effective complement to both traditional and next generation sequencing methodologies.

Identification of cardioviruses related to Theiler's murine encephalomyelitis virus in human infections.

Cardioviruses comprise a genus of picornaviruses that cause severe illnesses in rodents, but little is known about the prevalence, diversity, or spectrum of disease of such agents among humans. A single cardiovirus isolate, Saffold virus, was cultured in 1981 in stool from an infant with fever. Here, we describe the identification of a group of human cardioviruses that have been cloned directly from patient specimens, the first of which was detected using a pan-viral microarray in respiratory secretions from a child with influenza-like illness. Phylogenetic analysis of the nearly complete viral genome (7961 bp) revealed that this virus belongs to the Theiler's murine encephalomyelitis virus (TMEV) subgroup of cardioviruses and is most closely related to Saffold virus. Subsequent screening by RT-PCR of 719 additional respiratory specimens [637 (89%) from patients with acute respiratory illness] and 400 cerebrospinal fluid specimens from patients with neurological disease (aseptic meningitis, encephalitis, and multiple sclerosis) revealed no evidence of cardiovirus infection. However, screening of 751 stool specimens from 498 individuals in a gastroenteritis cohort resulted in the detection of 6 additional cardioviruses (1.2%). Although all 8 human cardioviruses (including Saffold virus) clustered together by phylogenetic analysis, significant sequence diversity was observed in the VP1 gene (66.9%-100% pairwise amino acid identities). These findings suggest that there exists a diverse group of novel human Theiler's murine encephalomyelitis virus-like cardioviruses that hitherto have gone largely undetected, are found primarily in the gastrointestinal tract, can be shed asymptomatically, and have potential links to enteric and extraintestinal disease.

Whole-genome analysis of mRNA decay in Plasmodium falciparum reveals a global lengthening of mRNA half-life during the intra-erythrocytic development cycle.

BACKGROUND: The rate of mRNA decay is an essential element of post-transcriptional regulation in all organisms. Previously, studies in several organisms found that the specific half-life of each mRNA is precisely related to its physiologic role, and plays an important role in determining levels of gene expression. RESULTS: We used a genome-wide approach to characterize mRNA decay in Plasmodium falciparum. We found that, globally, rates of mRNA decay increase dramatically during the asexual intra-erythrocytic developmental cycle. During the ring stage of the cycle, the average mRNA half-life was 9.5 min, but this was extended to an average of 65 min during the late schizont stage of development. Thus, a major determinant of mRNA decay rate appears to be linked to the stage of intra-erythrocytic development. Furthermore, we found specific variations in decay patterns superimposed upon the dominant trend of progressive half-life lengthening. These variations in decay pattern were frequently enriched for genes with specific cellular functions or processes. CONCLUSION: Elucidation of Plasmodium mRNA decay rates provides a key element for deciphering mechanisms of genetic control in this parasite, by complementing and extending previous mRNA abundance studies. Our results indicate that progressive stage-dependent decreases in mRNA decay rate function are a major determinant of mRNA accumulation during the schizont stage of intra-erythrocytic development. This type of genome-wide change in mRNA decay rate has not been observed in any other organism to date, and indicates that post-transcriptional regulation may be the dominant mechanism of gene regulation in P. falciparum.

E-Predict: a computational strategy for species identification based on observed DNA microarray hybridization patterns.

DNA microarrays may be used to identify microbial species present in environmental and clinical samples. However, automated tools for reliable species identification based on observed microarray hybridization patterns are lacking. We present an algorithm, E-Predict, for microarray-based species identification. E-Predict compares observed hybridization patterns with theoretical energy profiles representing different species. We demonstrate the application of the algorithm to viral detection in a set of clinical samples and discuss its relevance to other metagenomic applications.

Experimental evaluation of topological parameters determining protein-folding rates.

Recent work suggests that structural topology plays a key role in determining protein-folding rates and pathways. The refolding rates of small proteins that fold without intermediates are found to correlate with simple structural parameters such as relative contact order, long-range order, or the fraction of short-range contacts. To test and evaluate the role of structural topology experimentally, a set of circular permutants of the ribosomal protein S6 from Thermus thermophilus was analyzed. Despite a wide range of relative contact order, the permuted proteins all fold with similar rates. These results suggest that alternative topological parameters may better describe the role of topology in protein-folding rates.