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The article contributes to the ongoing discussion on relating information and communication technology (ICT) to development (D). The quest to relate ICT to D is a topic of open deliberation and critical scrutiny in ICT4D research communities. To enhance the understanding in this regard, we conducted a literature review. The review examines 80 articles to identify various development theories and the role of technologies in the development process. While scanning the articles, Sen's capability approach (CA) emerged as a suitable framework with which to explore the link between ICT and D. To show the relevance of the link, we used the CA as a guiding framework, and reanalyzed ten empirical case studies focusing on projects in remote and rural areas. Furthermore, the article suggests six gaps in the current research, and, accordingly, six areas for future research.

m Rapid development within the field of massive parallel sequencing (MPS) is about to bring this technology within reach for diagnostic microbiology laboratories. We wanted to explore its potential for improving diagnosis and understanding of polymicrobial infections, using bacterial brain abscesses as an example. We conducted a prospective nationwide study on bacterial brain abscesses. Fifty-two surgical samples were included over a 2-year period. The samples were categorized as either spontaneous intracerebral, spontaneous subdural, or postoperative. Bacterial 16S rRNA genes were amplified directly from the specimens and sequenced using Ion Torrent technology, with an average of 500,000 reads per sample. The results were compared to those from culture-and Sanger sequencing-based diagnostics. Compared to culture, MPS allowed for triple the number of bacterial identifications. Aggregatibacter aphrophilus, Fusobacterium nucleatum, and Streptococcus intermedius or combinations of them were found in all spontaneous polymicrobial abscesses. F. nucleatum was systematically detected in samples with anaerobic flora. The increased detection rate for Actinomyces spp. and facultative Gram-negative rods further revealed several species associations. We suggest that A. aphrophilus, F. nucleatum, and S. intermedius are key pathogens for the establishment of spontaneous polymicrobial brain abscesses. In addition, F. nucleatum seems to be important for the development of anaerobic flora. MPS can accurately describe polymicrobial specimens when a sufficient number of reads is used to compensate for unequal species concentrations and principles are defined to discard contaminant bacterial DNA in the subsequent data analysis. This will contribute to our understanding of how different types of polymicrobial infections develop. O ur understanding of polymicrobial infections has been hindered by our limited possibilities for describing them. Recent investigations of bacterial brain abscesses using universal amplification of the bacterial 16S rRNA gene, followed by Sanger sequencing of cloned amplicons, have revealed that only a fraction of the bacteria present are identified by culture (1, 2). Nevertheless, this approach has limitations when it comes to detecting smaller subpopulations in a multispecies community, unless very high numbers of clones are sequenced (3). This is problematic, since the species structure of an abscess may change over time and pathogens important for establishing the infection potentially remain at only low concentrations in the more mature abscesses. Furthermore, the species that are important for maintaining and expanding the abscess might primarily exist close to the abscess wall and do not necessarily dominate in the pus obtained by aspiration. Rapid development within the field of massive parallel sequencing technologies (MPS) is about to provide the diagnostic laboratories with tools that can characterize even the most complex microbial communities. The aim of the present study was to use recent adva...

Investigation of clinical samples by direct 16S rRNA gene sequencing provides the possibility to detect nonviable bacteria and bacteria with special growth requirements. This approach has been particularly valuable for the diagnosis of patients who have received antibiotics prior to sample collection. In specimens containing more than one bacterium, direct sequencing gives mixed chromatograms that complicate further interpretation. We designed an algorithm able to analyze these ambiguous chromatograms and implemented it as a Web-based service. The algorithm contains both a new base-calling procedure and a new database search procedure. 16S rRNA gene sequencing was performed on polybacterial suspensions prepared in the laboratory. The computer program identified all bacteria correctly to the species level in 23 out of 23 samples containing two different bacteria. For samples containing three different bacteria, correct identification to the species level was achieved for three out of five and to the genus level for five out of five.DNA sequencing has become a standard method in many microbiology laboratories. It is cheap, and the capacity for generating sequences is ever increasing. Identification of bacterial species from pure culture based on 16S rRNA gene sequencing is well established, and there is increasing interest in doing 16S rRNA gene sequencing directly on clinical samples (5,6,11,12). This provides the opportunity to identify bacteria that died during transportation or as a consequence of antibiotic treatment. The latest advances in PCR and sequencing technology also offer faster identification than standard phenotypical methods that depend on bacterial growth. This is of particular importance for slow-growing bacteria, bacteria with special growth requirements, and unusual bacteria for which reliable, standard phenotypic test batteries are not defined.One of the remaining problems for this approach is samples containing more than one bacterial species. For these samples, direct sequencing results in mixed chromatograms containing two or more fluorescent signals in positions where the 16S rRNA genes differ. The problem can be solved by separating the products from the first PCR by cloning or using gradient gel electrophoresis, but these methods are labor-intensive and not suitable for routine diagnostics.We have therefore designed an algorithm that sorts out the ambiguous signals from mixed chromatograms in order to identify the different contributing bacteria. The algorithm was implemented in the RipSeq computer program (iSentio) and was successfully used to analyze sequence data from mixed bacterial suspensions. MATERIALS AND METHODSAlgorithm. The interpretation of mixed chromatograms is dependent upon both correct reading of the chromatograms (base calling) and the subsequent matching procedure (search).Reading the chromatogram. Direct 16S rRNA gene sequencing of polymicrobial samples results in mixed chromatograms containing two or more fluorescent signals in positions where the 16S rRNA genes dif...

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