Tracking development assistance for health from China, 2007-2017.

INTRODUCTION: In recent years, China has increased its international engagement in health. Nonetheless, the lack of data on contributions has limited efforts to examine contributions from China. Existing estimates that track development assistance for health (DAH) from China have relied primarily on one dataset. Furthermore, little is known about the disbursing agencies especially the multilaterals through which contributions are disbursed and how these are changing across time. In this study, we generated estimates of DAH from China from 2007 through 2017 and disaggregated those estimates by disbursing agency and health focus area. METHODS: We identified the major government agencies providing DAH. To estimate DAH provided by each agency, we leveraged publicly available development assistance data in government agencies' budgets and financial accounts, as well as revenue statements from key international development agencies such as the WHO. We reported trends in DAH from China, disaggregated contributions by disbursing bilateral and multilateral agencies, and compared DAH from China with other traditional donors. We also compared these estimates with existing estimates. RESULTS: DAH provided by China grew dramatically, from US$323.1 million in 2007 to $652.3 million in 2017. During this period, 91.8% of DAH from China was disbursed through its bilateral agencies, including the Ministry of Commerce ($3.7 billion, 64.1%) and the National Health Commission ($917.1 million, 16.1%); the other 8.2% was disbursed through multilateral agencies including the WHO ($236.5 million, 4.1%) and the World Bank ($123.1 million, 2.2%). Relative to its level of economic development, China provided substantially more DAH than would be expected. However, relative to population size and government spending, China's contributions are modest. CONCLUSION: In the current context of plateauing in the growth rate of DAH contributions, China has the potential to contribute to future global health financing, especially financing for health system strengthening.

Discovery and profiling of small RNAs responsive to stress conditions in the plant pathogen Pectobacterium atrosepticum.

BACKGROUND: Small RNAs (sRNAs) have emerged as important regulatory molecules and have been studied in several bacteria. However, to date, there have been no whole-transcriptome studies on sRNAs in any of the Soft Rot Enterobacteriaceae (SRE) group of pathogens. Although the main ecological niches for these pathogens are plants, a significant part of their life cycle is undertaken outside their host within adverse soil environment. However, the mechanisms of SRE adaptation to this harsh nutrient-deficient environment are poorly understood. RESULTS: In the study reported herein, by using strand-specific RNA-seq analysis and in silico sRNA predictions, we describe the sRNA pool of Pectobacterium atrosepticum and reveal numerous sRNA candidates, including those that are induced during starvation-activated stress responses. Consequently, strand-specific RNA-seq enabled detection of 137 sRNAs and sRNA candidates under starvation conditions; 25 of these sRNAs were predicted for this bacterium in silico. Functional annotations were computationally assigned to 68 sRNAs. The expression of sRNAs in P. atrosepticum was compared under growth-promoting and starvation conditions: 68 sRNAs were differentially expressed with 47 sRNAs up-regulated under nutrient-deficient conditions. Conservation analysis using BLAST showed that most of the identified sRNAs are conserved within the SRE. Subsequently, we identified 9 novel sRNAs within the P. atrosepticum genome. CONCLUSIONS: Since many of the identified sRNAs are starvation-induced, the results of our study suggests that sRNAs play key roles in bacterial adaptive response. Finally, this work provides a basis for future experimental characterization and validation of sRNAs in plant pathogens.

Metagenomic analysis of the viral community in Namib Desert hypoliths.

Hypolithic microbial communities are specialized desert communities inhabiting the underside of translucent rocks. Here, we present the first study of the viral fraction of these communities isolated from the hyperarid Namib Desert. The taxonomic composition of the hypolithic viral communities was investigated and a functional assessment of the sequences determined. Phylotypic analysis showed that bacteriophages belonging to the order Caudovirales, in particular the family Siphoviridae, were most prevalent. Functional analysis and comparison with other metaviromes revealed a relatively high frequency of cell wall-degrading enzymes, ribonucleotide reductases (RNRs) and phage-associated genes. Phylogenetic analyses of terL and phoH marker genes indicated that many of the sequences were novel and distinct from known isolates, and the class distribution of the RNRs suggests that this is a novel environment. The composition of the viral hypolith fraction containing many Bacillus-infecting phages was not completely consistent with Namib hypolith phylotypic surveys of the bacterial hosts, in which the cyanobacterial genus Chroococcidiopsis was found to be dominant. This could be attributed to the lack of sequence information about hypolith viruses/bacteria in public databases or the possibility that hypolithic communities incorporate viruses from the surrounding soil.

IMA Genome-F 2: Ceratocystis manginecans, Ceratocystis moniliformis, Diplodia sapinea: Draft genome sequences of Diplodia sapinea, Ceratocystis manginecans, and Ceratocystis moniliformis.

The draft nuclear genomes of Diplodia sapinea, Ceratocystis moniliformis s. str., and C. manginecans are presented. Diplodia sapinea is an important shoot-blight and canker pathogen of Pinus spp., C. moniliformis is a saprobe associated with wounds on a wide range of woody angiosperms and C. manginecans is a serious wilt pathogen of mango and Acacia mangium. The genome size of D. sapinea is estimated at 36.97 Mb and contains 13 020 predicted genes. Ceratocystis moniliformis includes 25.43 Mb and is predicted to encode at least 6 832 genes. This is smaller than that reported for the mango wilt pathogen C. manginecans which is 31.71 Mb and is predicted to encode at least 7 494 genes. The latter is thus more similar to C. fimbriata s.str., the type species of the genus. The genome sequences presented here provide an important resource to resolve issues pertaining to the taxonomy, biology and evolution of these fungi.

High-level diversity of tailed phages, eukaryote-associated viruses, and virophage-like elements in the metaviromes of antarctic soils.

The metaviromes of two distinct Antarctic hyperarid desert soil communities have been characterized. Hypolithic communities, cyanobacterium-dominated assemblages situated on the ventral surfaces of quartz pebbles embedded in the desert pavement, showed higher virus diversity than surface soils, which correlated with previous bacterial community studies. Prokaryotic viruses (i.e., phages) represented the largest viral component (particularly Mycobacterium phages) in both habitats, with an identical hierarchical sequence abundance of families of tailed phages (Siphoviridae > Myoviridae > Podoviridae). No archaeal viruses were found. Unexpectedly, cyanophages were poorly represented in both metaviromes and were phylogenetically distant from currently characterized cyanophages. Putative phage genomes were assembled and showed a high level of unaffiliated genes, mostly from hypolithic viruses. Moreover, unusual gene arrangements in which eukaryotic and prokaryotic virus-derived genes were found within identical genome segments were observed. Phycodnaviridae and Mimiviridae viruses were the second-most-abundant taxa and more numerous within open soil. Novel virophage-like sequences (within the Sputnik clade) were identified. These findings highlight high-level virus diversity and novel species discovery potential within Antarctic hyperarid soils and may serve as a starting point for future studies targeting specific viral groups.

Analysis of the Pantoea ananatis pan-genome reveals factors underlying its ability to colonize and interact with plant, insect and vertebrate hosts.

BACKGROUND: Pantoea ananatis is found in a wide range of natural environments, including water, soil, as part of the epi- and endophytic flora of various plant hosts, and in the insect gut. Some strains have proven effective as biological control agents and plant-growth promoters, while other strains have been implicated in diseases of a broad range of plant hosts and humans. By analysing the pan-genome of eight sequenced P. ananatis strains isolated from different sources we identified factors potentially underlying its ability to colonize and interact with hosts in both the plant and animal Kingdoms. RESULTS: The pan-genome of the eight compared P. ananatis strains consisted of a core genome comprised of 3,876 protein coding sequences (CDSs) and a sizeable accessory genome consisting of 1,690 CDSs. We estimate that ~106 unique CDSs would be added to the pan-genome with each additional P. ananatis genome sequenced in the future. The accessory fraction is derived mainly from integrated prophages and codes mostly for proteins of unknown function. Comparison of the translated CDSs on the P. ananatis pan-genome with the proteins encoded on all sequenced bacterial genomes currently available revealed that P. ananatis carries a number of CDSs with orthologs restricted to bacteria associated with distinct hosts, namely plant-, animal- and insect-associated bacteria. These CDSs encode proteins with putative roles in transport and metabolism of carbohydrate and amino acid substrates, adherence to host tissues, protection against plant and animal defense mechanisms and the biosynthesis of potential pathogenicity determinants including insecticidal peptides, phytotoxins and type VI secretion system effectors. CONCLUSIONS: P. ananatis has an 'open' pan-genome typical of bacterial species that colonize several different environments. The pan-genome incorporates a large number of genes encoding proteins that may enable P. ananatis to colonize, persist in and potentially cause disease symptoms in a wide range of plant and animal hosts.

Niche-dependent genetic diversity in Antarctic metaviromes.

The metaviromes from 2 different Antarctic terrestrial soil niches have been analyzed. Both hypoliths (microbial assemblages beneath transluscent rocks) and surrounding open soils showed a high level diversity of tailed phages, viruses of algae and amoeba, and virophage sequences. Comparisons of other global metaviromes with the Antarctic libraries showed a niche-dependent clustering pattern, unrelated to the geographical origin of a given metavirome. Within the Antarctic open soil metavirome, a putative circularly permuted, ∼42kb dsDNA virus genome was annotated, showing features of a temperate phage possessing a variety of conserved protein domains with no significant taxonomic affiliations in current databases.

Lentiviral vector common integration sites in preclinical models and a clinical trial reflect a benign integration bias and not oncogenic selection.

A recent clinical trial for adrenoleukodystrophy (ALD) showed the efficacy and safety of lentiviral vector (LV) gene transfer in hematopoietic stem progenitor cells. However, several common insertion sites (CIS) were found in patients' cells, suggesting that LV integrations conferred a selective advantage. We performed high-throughput LV integration site analysis on human hematopoietic stem progenitor cells engrafted in immunodeficient mice and found the same CISs reported in patients with ALD. Strikingly, most CISs in our experimental model and in patients with ALD cluster in megabase-wide chromosomal regions of high LV integration density. Conversely, cancer-triggering integrations at CISs found in tumor cells from γ-retroviral vector-based clinical trials and oncogene-tagging screenings in mice always target a single gene and are contained in narrow genomic intervals. These findings imply that LV CISs are produced by an integration bias toward specific genomic regions rather than by oncogenic selection.

Ab initio and homology based prediction of protein domains by recursive neural networks.

BACKGROUND: Proteins, especially larger ones, are often composed of individual evolutionary units, domains, which have their own function and structural fold. Predicting domains is an important intermediate step in protein analyses, including the prediction of protein structures. RESULTS: We describe novel systems for the prediction of protein domain boundaries powered by Recursive Neural Networks. The systems rely on a combination of primary sequence and evolutionary information, predictions of structural features such as secondary structure, solvent accessibility and residue contact maps, and structural templates, both annotated for domains (from the SCOP dataset) and unannotated (from the PDB). We gauge the contribution of contact maps, and PDB and SCOP templates independently and for different ranges of template quality. We find that accurately predicted contact maps are informative for the prediction of domain boundaries, while the same is not true for contact maps predicted ab initio. We also find that gap information from PDB templates is informative, but, not surprisingly, less than SCOP annotations. We test both systems trained on templates of all qualities, and systems trained only on templates of marginal similarity to the query (less than 25% sequence identity). While the first batch of systems produces near perfect predictions in the presence of fair to good templates, the second batch outperforms or match ab initio predictors down to essentially any level of template quality.We test all systems in 5-fold cross-validation on a large non-redundant set of multi-domain and single domain proteins. The final predictors are state-of-the-art, with a template-less prediction boundary recall of 50.8% (precision 38.7%) within +/- 20 residues and a single domain recall of 80.3% (precision 78.1%). The SCOP-based predictors achieve a boundary recall of 74% (precision 77.1%) again within +/- 20 residues, and classify single domain proteins as such in over 85% of cases, when we allow a mix of bad and good quality templates. If we only allow marginal templates (max 25% sequence identity to the query) the scores remain high, with boundary recall and precision of 59% and 66.3%, and 80% of all single domain proteins predicted correctly. CONCLUSION: The systems presented here may prove useful in large-scale annotation of protein domains in proteins of unknown structure. The methods are available as public web servers at the address: http://distill.ucd.ie/shandy/ and we plan on running them on a multi-genomic scale and make the results public in the near future.