Molecular characterization of the microbial species that colonize human ileal and colonic mucosa by using 16S rDNA sequence analysis

Aim: The aim of this study was to characterize the bacterial community adhering to the mucosa of the terminal ileum, and proximal and distal colon of the human digestive tract. Methods and Results: Pinch samples of the terminal ileum, proximal and distal colon were taken from a healthy 35-year-old, and a 68-year-old subject with mild diverticulosis. The 16S rDNA genes were amplified using a low number of PCR cycles, cloned, and sequenced. In total, 361 sequences were obtained comprising 70 operational taxonomic units (OTU), with a calculated coverage of 82.6%. Twenty-three per cent of OTU were common to the terminal ileum, proximal colon and distal colon, but 14% OTU were only found in the terminal ileum, and 43% were only associated with the proximal or distal colon. The most frequently represented clones were from the Clostridium group XIVa (24.7%), and the Bacteroidetes (Cytophaga-Flavobacteria-Bacteroides ) cluster (27.7%). Conclusion: Comparison of 16S rDNA clone libraries of the hindgut across mammalian species confirms that the distribution of phylogenetic groups is similar irrespective of the host species. Lesser site-related differences within groups or clusters of organisms, are probable. Significance and Impact: This study provides further evidence of the distribution of the bacteria on the mucosal surfaces of the human hindgut. Data contribute to the benchmarking of the microbial composition of the human digestive tract.

The applicability of recurrent neural networks for biological sequence analysis

Selection of machine learning techniques requires a certain sensitivity to the requirements of the problem. In particular, the problem can be made more tractable by deliberately using algorithms that are biased toward solutions of the requisite kind. In this paper, we argue that recurrent neural networks have a natural bias toward a problem domain of which biological sequence analysis tasks are a subset. We use experiments with synthetic data to illustrate this bias. We then demonstrate that this bias can be exploitable using a data set of protein sequences containing several classes of subcellular localization targeting peptides. The results show that, compared with feed forward, recurrent neural networks will generally perform better on sequence analysis tasks. Furthermore, as the patterns within the sequence become more ambiguous, the choice of specific recurrent architecture becomes more critical.

Cloning and sequence analysis of pituitary prolactin cDNA from the northern brown bandicoot (Isoodon macrourus)

The nuclectide sequence for pituitary prolactin cDNA from the marsupial bandicoot (Isoodon macrourus) was determined by reverse transcription-polymerase chain reaction and 5'/3' rapid amplification of cDNA ends. The deduced amino acid sequence showed high sequence identity with brushtail possum prolactin (95%) and all of the expected structural features of a quadruped prolactin. A prolactin gene tree was constructed and rates of evolution calculated for bandicoot, possum, opossum and several mammalian and non-mammalian prolactins. Bootstrap analysis provided strong support for marsupials as a sister group with eutherian mammals and weak support for opossum and bandicoot as an independent grouping from the brushtail possum. The rates of molecular evolution for marsupial prolactins were comparable to the slow rate seen in the majority of quadruped prolactins that have been sequenced. (c) 2005 Elsevier Inc. All rights reserved.

Seizure detection algorithm for neonates based on wave-sequence analysis

Objective: The description and evaluation of the performance of a new real-time seizure detection algorithm in the newborn infant. Methods: The algorithm includes parallel fragmentation of EEG signal into waves; wave-feature extraction and averaging; elementary, preliminary and final detection. The algorithm detects EEG waves with heightened regularity, using wave intervals, amplitudes and shapes. The performance of the algorithm was assessed with the use of event-based and liberal and conservative time-based approaches and compared with the performance of Gotman's and Liu's algorithms. Results: The algorithm was assessed on multi-channel EEG records of 55 neonates including 17 with seizures. The algorithm showed sensitivities ranging 83-95% with positive predictive values (PPV) 48-77%. There were 2.0 false positive detections per hour. In comparison, Gotman's algorithm (with 30 s gap-closing procedure) displayed sensitivities of 45-88% and PPV 29-56%; with 7.4 false positives per hour and Liu's algorithm displayed sensitivities of 96-99%, and PPV 10-25%; with 15.7 false positives per hour. Conclusions: The wave-sequence analysis based algorithm displayed higher sensitivity, higher PPV and a substantially lower level of false positives than two previously published algorithms. Significance: The proposed algorithm provides a basis for major improvements in neonatal seizure detection and monitoring. Published by Elsevier Ireland Ltd. on behalf of International Federation of Clinical Neurophysiology.

GANN: Genetic algorithm neural networks for the detection of conserved combinations of features in DNA

Background: The multitude of motif detection algorithms developed to date have largely focused on the detection of patterns in primary sequence. Since sequence-dependent DNA structure and flexibility may also play a role in protein-DNA interactions, the simultaneous exploration of sequence-and structure-based hypotheses about the composition of binding sites and the ordering of features in a regulatory region should be considered as well. The consideration of structural features requires the development of new detection tools that can deal with data types other than primary sequence. Results: GANN ( available at http://bioinformatics.org.au/gann) is a machine learning tool for the detection of conserved features in DNA. The software suite contains programs to extract different regions of genomic DNA from flat files and convert these sequences to indices that reflect sequence and structural composition or the presence of specific protein binding sites. The machine learning component allows the classification of different types of sequences based on subsamples of these indices, and can identify the best combinations of indices and machine learning architecture for sequence discrimination. Another key feature of GANN is the replicated splitting of data into training and test sets, and the implementation of negative controls. In validation experiments, GANN successfully merged important sequence and structural features to yield good predictive models for synthetic and real regulatory regions. Conclusion: GANN is a flexible tool that can search through large sets of sequence and structural feature combinations to identify those that best characterize a set of sequences.

Development of a DNA-based method for detection and identification of Phytophthora species

Phytophthora diseases cause major losses to agricultural and horticultural production in Australia and worldwide. Most Phytophthora diseases are soilborne and difficult to control, making disease prevention an important component of many disease management strategies. Detection and identification of the causal agent, therefore, is an essential part of effective disease management. This paper describes the development and validation of a DNA-based diagnostic assay that can detect and identify 27 different Phytophthora species. We have designed PCR primers that are specific to the genus Phytophthora. The resulting amplicon after PCR is subjected to digestion by restriction enzymes to yield a specific restriction pattern or fingerprint unique to each species. The restriction patterns are compared with a key comprising restriction patterns of type specimens or representative isolates of 27 different Phytophthora species. A number of fundamental issues, such as genetic diversity within and among species which underpin the development and validation of DNA-based diagnostic assays, are addressed in this paper.

Phylogenetic and physiological characterization of a heterotrophic, chemolithoautotrophic Thiothrix strain isolated from activated sludge

The sheathed filamentous bacterium known as strain CT3, isolated by micromanipulation from an activated sludge treatment plant in Italy, is a member of the genus Thiothrix in the gamma-Proteobacteria according to 16S rDNA sequence analysis. The closest phylogenetic neighbours of strain CT3 are strains I and Q(T), which were also isolated from activated sludge and belong to the species Thiothrix fructosivorans. These strains have respectively 99.2 and 99.4 % similarity to CT3 by 16S rDNA sequence comparison. CT3 shows 63-67 % DNA-DNA hybridization with strain I, which is the only currently viable strain of T. fructosivorans. CT3 is the second strain in the genus Thiothrix that has been shown to be capable of growing autotrophically with reduced sulfur compounds as the sole energy source; autotrophy was also confirmed in strain I. The first reported chemolithoautotrophic isolate of this genus was a strain of 'Thiothrix ramosa' that was isolated from a hydrogen sulfide spring and is morphologically distinguishable from all other described strains of Thiothrix, including CT3. CT3 is an aerobic organism that is non-fermentative, not capable of denitrification and able to grow heterotrophically. Autotrophy in the genus Thiothrix should be investigated more fully to better define the taxonomy of this genus.

Highly organized structure in the non-coding region of the psbA minicircle from clade C Symbiodinium

The chloroplast genes of dinoflagellates are distributed among small, circular dsDNA molecules termed minicircles. In this paper, we describe the structure of the non-coding region of the psbA minicircle from Symbiodinium. DNA sequence was obtained from five Symbiodinium strains obtained from four different coral host species (Goniopora tenuidens, Heliofungia actiniformis, Leptastrea purpurea and Pocillopora damicornis), which had previously been determined to be closely related using LSU rDNA region D1/D2 sequence analysis. Eight distinct sequence blocks, consisting of four conserved cores interspersed with two metastable regions and flanked by two variable regions, occurred at similar positions in all strains. Inverted repeats (IRs) occurred in tandem or 'twin' formation within two of the four cores. The metastable regions also consisted of twin IRs and had modular behaviour, being either fully present or completely absent in the different strains. These twin IRs are similar in sequence to double-hairpin elements (DHEs) found in the mitochondrial genomes of some fungi, and may be mobile elements or may serve a functional role in recombination or replication. Within the central unit (consisting of the cores plus the metastable regions), all IRs contained perfect sequence inverses, implying they are highly evolved. IRs were also present outside the central unit but these were imperfect and possessed by individual strains only. A central adenine-rich sequence most closely resembled one in the centre of the non-coding part of Amphidinium operculatum minicircles, and is a potential origin of replication. Sequence polymorphism was extremely high in the variable regions, suggesting that these regions may be useful for distinguishing strains that cannot be differentiated using molecular markers currently available for Symbiodinium.

Identification and cloning of the gene encoding BmpC: an outer-membrane lipoprotein associated with Brachyspira pilosicoli membrane vesicles

The intestinal spirochaete Brachyspira pilosicoli causes colitis in a wide variety of host species. Little is known about the structure or protein constituents of the B. pilosicoli outer membrane (OM). To identify surface-exposed proteins in this species, membrane vesicles were isolated from B. pilosicoli strain 95-1000 cells by osmotic lysis in dH(2)O followed by isopycnic centrifugation in sucrose density gradients. The membrane vesicles were separated into a high-density fraction (HDMV; p = 1.18 g CM-3) and a low-density fraction (LDMV; rho=1.12 g cm(-3)). Both fractions were free of flagella and soluble protein contamination. LDMV contained predominantly OM markers (lipo-oligosaccharide and a 29 kDa B. pilosicoli OM protein) and was used as a source of antigens to produce mAbs. Five B. pilosicoli-specific mAbs reacting with proteins with molecular masses of 23, 24, 35, 61 and 79 kDa were characterized. The 23 kDa protein was only partially soluble in Triton X-114, whereas the 24 and 35 kDa proteins were enriched in the detergent phase, implying that they were integral membrane proteins or lipoproteins. All three proteins were localized to the B. pilosicoli OM by immunogold labelling using specific mAbs. The gene encoding the abundant, surface-exposed 23 kDa protein was identified by screening a B. pilosicoli 95-1000 genome library with the mAb and was expressed in Escherichia coli. Sequence analysis showed that it encoded a unique lipoprotein, designated BmpC. Recombinant BmpC partitioned predominantly in the OM fraction of E. coli strain SOLR. The mAb to BmpC was used to screen a collection of 13 genetically heterogeneous strains of B. pilosicoli isolated from five different host species. Interestingly, only strain 95-1000 was reactive with the mAb, indicating that either the surface-exposed epitope on BmpC is variable between strains or that the protein is restricted in its distribution within B. pilosicoli.

Characterization of Streptococcus bovis from the rumen of the dromedary camel and Rusa deer

Aims: Isolation and characterization of Streptococcus bovis from the dromedary camel and Rusa deer. Methods and Results: Bacteria were isolated from the rumen contents of four camels and two deer fed lucerne hay by culturing on the semi-selective medium MRS agar. Based on Gram morphology and RFLP analysis seven isolates, MPR1, MPR2, MPR3, MPR4, MPR5, RD09 and RD11 were selected and putatively identified as Streptococcus. The identity of these isolates was later confirmed by comparative DNA sequence analysis of the 16S rRNA gene with the homologous sequence from S. bovis strains, JB1, C14b1, NCFB2476, SbR1, SbR7 and Sb5, from cattle and sheep, and the Streptococcus equinus strain NCD01037T. The percentage similarity amongst all strains was >99%, confirming the identification of the camel isolates as S. bovis. The strains were further characterized by their ability to utilize a range of carbohydrates, the production of volatile fatty acids (VFA) and lactate and the determination of the doubling time in basal medium 10 supplemented with glucose. All the isolates produced L-lactate as a major fermentation end product, while four of five camel isolates produced VFA. The range of carbohydrates utilized by all the strains tested, including those from cattle and sheep were identical, except that all camel isolates and the deer isolate RD11 were additionally able to utilize arabinose. Conclusions: Streptococcus bovis was successfully isolated from the rumen of camels and deer, and shown by molecular and biochemical characterization to be almost identical to S. bovis isolates from cattle and sheep. Significance and Impact of the Study: Streptococcus bovis is considered a key lactic acid producing bacterium from the gastrointestinal tract of ruminants, and has been implicated as a causative agent of lactic acidosis. This study is the first report of the isolation and characterization of S. bovis from the dromedary camel and Rusa deer, and suggests a major contributive role of this bacterium to fermentative acidosis.

The genetic diversity of lactic acid producing bacteria in the equine gastrointestinal tract

Seventy-two lactic acid producing bacterial isolates (excluding streptococci) were cultured from the gastrointestinal tract of six horses. Two of the horses were orally dosed with raftilose to induce lactic acidosis and laminitis while the remaining four were maintained on a roughage diet. Near complete 16S rDNA was amplified by PCR from the genomic DNA of each isolate. Following RFLP analysis with the restriction enzymes MboI, HhaI and HinfI, the PCR products from the IS isolates that produced L- and/or D-lactate were subsequently cloned and sequenced. DNA sequence analysis indicated that the majority of the isolates were closely related to species within the genus Lactobacillus, including Lactobacillus salivarius, Lactobacillus mucosae and Lactobacillus delbrueckii. Four isolates were closely related to Mitsuokella jalaludinii. Lactic acid producing bacteria (LAB) from the equine gastrointestinal tract was dominated by representatives from the genus Lactobacillus, but also included D-lactate-producing bacteria closely related to M. jalaludinii. Identification and characterization of LAB from the equine gastrointestinal tract should contribute to our understanding and management of fermentative acidosis, ulceration of the stomach and laminitis. (c) 2005 Federation of European Microbiological Societies. Published by Elsevier B.V. All rights reserved.