Mechanism for Multiple Ligand Recognition by the Human Transferrin Receptor

Transferrin receptor 1 (TfR) plays a critical role in cellular iron import for most higher organisms. Cell surface TfR binds to circulating iron-loaded transferrin (Fe-Tf) and transports it to acidic endosomes, where low pH promotes iron to dissociate from transferrin (Tf) in a TfR-assisted process. The iron-free form of Tf (apo-Tf) remains bound to TfR and is recycled to the cell surface, where the complex dissociates upon exposure to the slightly basic pH of the blood. Fe-Tf competes for binding to TfR with HFE, the protein mutated in the iron-overload disease hereditary hemochromatosis. We used a quantitative surface plasmon resonance assay to determine the binding affinities of an extensive set of site-directed TfR mutants to HFE and Fe-Tf at pH 7.4 and to apo-Tf at pH 6.3. These results confirm the previous finding that Fe-Tf and HFE compete for the receptor by binding to an overlapping site on the TfR helical domain. Spatially distant mutations in the TfR protease-like domain affect binding of Fe-Tf, but not iron-loaded Tf C-lobe, apo-Tf, or HFE, and mutations at the edge of the TfR helical domain affect binding of apo-Tf, but not Fe-Tf or HFE. The binding data presented here reveal the binding footprints on TfR for Fe-Tf and apo-Tf. These data support a model in which the Tf C-lobe contacts the TfR helical domain and the Tf N-lobe contacts the base of the TfR protease-like domain. The differential effects of some TfR mutations on binding to Fe-Tf and apo-Tf suggest differences in the contact points between TfR and the two forms of Tf that could be caused by pH-dependent conformational changes in Tf, TfR, or both. From these data, we propose a structure-based model for the mechanism of TfR-assisted iron release from Fe-Tf

Characterization and cloning of fasciclin I and fasciclin II glycoproteins in the grasshopper

Monoclonal antibodies were previously used to identify two glycoproteins, called fasciclin I and II (70 and 95 kDa, respectively), which are expressed on different subsets of axon fascicles in the grasshopper (Schistocerca americana) embryo. Here the monoclonal antibodies were used to purify these two membrane-associated glycoproteins for further characterization. Fasciclin II appears to be an integral membrane protein, where fasciclin I is an extrinsic membrane protein. The amino acid sequences of the amino terminus and fragments of both proteins were determined. Using synthetic oligonucleotide probes and antibody screening, we isolated genomic and cDNA clones. Partial DNA sequences of these clones indicate that they encode fasciclins I and II

Spatial models for the rational allocation of routinely distributed bed nets to public health facilities in Western Kenya

BACKGROUND: In high to moderate malaria transmission areas of Kenya, long-lasting insecticidal nets (LLINs) are provided free of charge to pregnant women and infants during routine antenatal care (ANC) and immunization respectively. Quantities of LLINs distributed to clinics are quantified based on a combination of monthly consumption data and population size of target counties. However, this approach has been shown to lead to stock-outs in targeted clinics. In this study, a novel LLINs need quantification approach for clinics in the routine distribution system was developed. The estimated need was then compared to the actual allocation to identify potential areas of LLIN over- or under-allocation in the high malaria transmission areas of Western Kenya. METHODS: A geocoded database of public health facilities was developed and linked to monthly LLIN allocation. A network analysis approach was implemented using the location of all public clinics and topographic layers to model travel time. Estimated travel time, socio-economic and ANC attendance data were used to model clinic catchment areas and the probability of ANC service use within these catchments. These were used to define the number of catchment population who were likely to use these clinics for the year 2015 equivalent to LLIN need. Actual LLIN allocation was compared with the estimated need. Clinics were then classified based on whether allocation matched with the need, and if not, whether they were over or under-allocated. RESULTS: 888 (70%) public health facilities were allocated 591,880 LLINs in 2015. Approximately 682,377 (93%) pregnant women and infants were likely to have attended an LLIN clinic. 36% of the clinics had more LLIN than was needed (over-allocated) while 43% had received less (under-allocated). Increasing efficiency of allocation by diverting over supply of LLIN to clinics with less stock and fully covering 43 clinics that did not receive nets in 2015 would allow for complete matching of need with distribution. CONCLUSION: The proposed spatial modelling framework presents a rationale for equitable allocation of routine LLINs and could be used for quantification of other maternal and child health commodities applicable in different settings. Western Kenya region received adequate LLINs for routine distribution in line with government of Kenya targets, however, the model shows important inefficiencies in the allocation of the LLINs at clinic level

A spatial national health facility database for public health sector planning in Kenya in 2008

<p>Abstract</p> <p>Background</p> <p>Efforts to tackle the enormous burden of ill-health in low-income countries are hampered by weak health information infrastructures that do not support appropriate planning and resource allocation. For health information systems to function well, a reliable inventory of health service providers is critical. The spatial referencing of service providers to allow their representation in a geographic information system is vital if the full planning potential of such data is to be realized.</p> <p>Methods</p> <p>A disparate series of contemporary lists of health service providers were used to update a public health facility database of Kenya last compiled in 2003. These new lists were derived primarily through the national distribution of antimalarial and antiretroviral commodities since 2006. A combination of methods, including global positioning systems, was used to map service providers. These spatially-referenced data were combined with high-resolution population maps to analyze disparity in geographic access to public health care.</p> <p>Findings</p> <p>The updated 2008 database contained 5,334 public health facilities (67% ministry of health; 28% mission and nongovernmental organizations; 2% local authorities; and 3% employers and other ministries). This represented an overall increase of 1,862 facilities compared to 2003. Most of the additional facilities belonged to the ministry of health (79%) and the majority were dispensaries (91%). 93% of the health facilities were spatially referenced, 38% using global positioning systems compared to 21% in 2003. 89% of the population was within 5 km Euclidean distance to a public health facility in 2008 compared to 71% in 2003. Over 80% of the population outside 5 km of public health service providers was in the sparsely settled pastoralist areas of the country.</p> <p>Conclusion</p> <p>We have shown that, with concerted effort, a relatively complete inventory of mapped health services is possible with enormous potential for improving planning. Expansion in public health care in Kenya has resulted in significant increases in geographic access although several areas of the country need further improvements. This information is key to future planning and with this paper we have released the digital spatial database in the public domain to assist the Kenyan Government and its partners in the health sector.</p

FUSE Measurements of Far Ultraviolet Extinction. I. Galactic Sight Lines

We present extinction curves that include data down to far ultraviolet wavelengths (FUV; 1050 - 1200 A) for nine Galactic sight lines. The FUV extinction was measured using data from the Far Ultraviolet Spectroscopic Explorer. The sight lines were chosen for their unusual extinction properties in the infrared through the ultraviolet; that they probe a wide range of dust environments is evidenced by the large spread in their measured ratios of total-to-selective extinction, R_V = 2.43 - 3.81. We find that extrapolation of the Fitzpatrick & Massa relationship from the ultraviolet appears to be a good predictor of the FUV extinction behavior. We find that predictions of the FUV extinction based upon the Cardelli, Clayton & Mathis (CCM) dependence on R_V give mixed results. For the seven extinction curves well represented by CCM in the infrared through ultraviolet, the FUV extinction is well predicted in three sight lines, over-predicted in two sight lines, and under-predicted in 2 sight lines. A Maximum Entropy Method analysis using a simple three component grain model shows that seven of the nine sight lines in the study require a larger fraction of grain materials to be in dust when FUV extinction is included in the models. Most of the added grain material is in the form of small (radii < 200 A) grains.Comment: Accepted for publication in the Astrophysical Journal. 31 pages with 7 figure

Quantifying full phenological event distributions reveals simultaneous advances, temporal stability and delays in spring and autumn migration timing in long-distance migratory birds

Acknowledgements We thank all Fair Isle Bird Observatory staff and volunteers for help with data collection and acknowledge the foresight of George Waterston and Ken Williamson in instigating the observatory and census methodology. We thank all current and previous directors of Fair Isle Bird Observatory Trust for their contributions, particularly Dave Okill and Mike Wood for their stalwart support for the long-term data collection and for the current analyses. Dawn Balmer and Ian Newton provided helpful guidance on manuscript drafts. We thank Ally Phillimore and two anonymous referees for helpful comments. This study would have been impossible without the Fair Isle community's invaluable support and patience over many decades, which is very gratefully acknowledged. WTSM and JMR designed and undertook analyses, wrote the paper and contributed to data collection and compilation, MB contributed to analysis and editing, all other authors oversaw and undertook data collection and compilation and contributed to editing.Peer reviewedPostprin

Structure-guided engineering of Lactococcus lactis alcohol dehydrogenase LlAdhA for improved conversion of isobutyraldehyde to isobutanol

We have determined the X-ray crystal structures of the NADH-dependent alcohol dehydrogenase LlAdhA from Lactococcus lactis and its laboratory-evolved variant LlAdhA^(RE1) at 1.9 Å and 2.5 Å resolution, respectively. LlAdhA^(RE1), which contains three amino acid mutations (Y50F, I212T, and L264V), was engineered to increase the microbial production of isobutanol (2-methylpropan-1-ol) from isobutyraldehyde (2-methylpropanal). Structural comparison of LlAdhA and LlAdhA^(RE1) indicates that the enhanced activity on isobutyraldehyde stems from increases in the protein's active site size, hydrophobicity, and substrate access. Further structure-guided mutagenesis generated a quadruple mutant (Y50F/N110S/I212T/L264V), whose K_M for isobutyraldehyde is ∼17-fold lower and catalytic efficiency (k_(cat)/K_M) is ∼160-fold higher than wild-type LlAdhA. Combining detailed structural information and directed evolution, we have achieved significant improvements in non-native alcohol dehydrogenase activity that will facilitate the production of next-generation fuels such as isobutanol from renewable resources

Spatial prediction of Plasmodium falciparum prevalence in Somalia

BACKGROUND Maps of malaria distribution are vital for optimal allocation of resources for anti-malarial activities. There is a lack of reliable contemporary malaria maps in endemic countries in sub-Saharan Africa. This problem is particularly acute in low malaria transmission countries such as those located in the horn of Africa. METHODS Data from a national malaria cluster sample survey in 2005 and routine cluster surveys in 2007 were assembled for Somalia. Rapid diagnostic tests were used to examine the presence of Plasmodium falciparum parasites in finger-prick blood samples obtained from individuals across all age-groups. Bayesian geostatistical models, with environmental and survey covariates, were used to predict continuous maps of malaria prevalence across Somalia and to define the uncertainty associated with the predictions. RESULTS For analyses the country was divided into north and south. In the north, the month of survey, distance to water, precipitation and temperature had no significant association with P. falciparum prevalence when spatial correlation was taken into account. In contrast, all the covariates, except distance to water, were significantly associated with parasite prevalence in the south. The inclusion of covariates improved model fit for the south but not for the north. Model precision was highest in the south. The majority of the country had a predicted prevalence of or = 5% prevalence were predominantly in the south. CONCLUSION The maps showed that malaria transmission in Somalia varied from hypo- to meso-endemic. However, even after including the selected covariates in the model, there still remained a considerable amount of unexplained spatial variation in parasite prevalence, indicating effects of other factors not captured in the study. Nonetheless the maps presented here provide the best contemporary information on malaria prevalence in Somalia.AMN is supported by the Wellcome Trust as a Research Training Fellow (#081829). SIH is supported by the Wellcome Trust as Senior Research Fellow (#079091). RWS is supported by the Wellcome Trust as Principal Research Fellow (#079081). AMN, SIH and RWS acknowledge the support of the Kenyan Medical Research Institute

A rapid and reproducible picture of open access health facility data in Africa to support the COVID-19 response

Background: Open data on the locations and services provided by health facilities in some countries have allowed the development of software tools contributing to COVID-19 response. The UN and WHO encourage countries to make health facility location data open, to encourage use and improvement. We provide a summary of open access health facility location data in Africa using re-useable code. We aim to support data analysts developing software tools to address COVID-19 response in individual countries. In Africa there are currently three main sources of such data; 1) direct from national ministries of health, 2) a database for sub-Saharan Africa collated and published by a team from KEMRI-Wellcome Trust Research Programme and now hosted by WHO, and 3) The Global Healthsites Mapping Project in collaboration with OpenStreetMap. Methods: We searched for and documented official national facility location data that were openly available. We developed re-useable open-source R code to summarise and visualise facility location data by country from the three sources. This re-useable code is used to provide a web user interface allowing data exploration through maps and plots of facility type. Results: Out of 53 African countries, seven provide an official open facility list that can be downloaded and analysed reproducibly. Considering all three sources, there are over 185,000 health facility locations available for Africa. However, there are differences and overlaps between sources and a lack of data on capacities and service provision. Conclusions: We suggest that these summaries and tools will encourage greater use of existing health facility location data, incentivise further improvements in the provision of those data by national suppliers, and encourage collaboration within wider data communities. The tools are a part of the afrimapr project, actively developing R building blocks to facilitate the use of health data in Africa

Spatial prediction of Plasmodium falciparum prevalence in Somalia

BACKGROUND: Maps of malaria distribution are vital for optimal allocation of resources for anti-malarial activities. There is a lack of reliable contemporary malaria maps in endemic countries in sub-Saharan Africa. This problem is particularly acute in low malaria transmission countries such as those located in the horn of Africa. METHODS: Data from a national malaria cluster sample survey in 2005 and routine cluster surveys in 2007 were assembled for Somalia. Rapid diagnostic tests were used to examine the presence of Plasmodium falciparum parasites in finger-prick blood samples obtained from individuals across all age-groups. Bayesian geostatistical models, with environmental and survey covariates, were used to predict continuous maps of malaria prevalence across Somalia and to define the uncertainty associated with the predictions. RESULTS: For analyses the country was divided into north and south. In the north, the month of survey, distance to water, precipitation and temperature had no significant association with P. falciparum prevalence when spatial correlation was taken into account. In contrast, all the covariates, except distance to water, were significantly associated with parasite prevalence in the south. The inclusion of covariates improved model fit for the south but not for the north. Model precision was highest in the south. The majority of the country had a predicted prevalence of &lt; 5%; areas with &gt; or = 5% prevalence were predominantly in the south. CONCLUSION: The maps showed that malaria transmission in Somalia varied from hypo- to meso-endemic. However, even after including the selected covariates in the model, there still remained a considerable amount of unexplained spatial variation in parasite prevalence, indicating effects of other factors not captured in the study. Nonetheless the maps presented here provide the best contemporary information on malaria prevalence in Somalia