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/lp/springer_journal/rivers-as-carriers-and-potential-sentinels-for-burkholderia-iaB49mvjos
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- Springer Journals
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- Copyright © 2018 by The Author(s)
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- Science, Humanities and Social Sciences, multidisciplinary; Science, Humanities and Social Sciences, multidisciplinary; Science, multidisciplinary
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- 2045-2322
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- 10.1038/s41598-018-26684-y
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Abstract
www.nature.com/scientificreports OPEN Rivers as carriers and potential sentinels for Burkholderia pseudomallei in Laos Received: 30 January 2018 1,2,3 4 5 1 Rosalie E. Zimmermann , Olivier Ribolzi , Alain Pierret , Sayaphet Rattanavong , 1,6 1,6 1 4 2 Accepted: 17 May 2018 Matthew T. Robinson , Paul N. Newton , Viengmon Davong , Yves Auda , Jakob Zopfi & 1,6,7 Published: xx xx xxxx David A. B. Dance Burkholderia pseudomallei, causative agent of the often fatal disease melioidosis, dwells in tropical soils and has been found in freshwater bodies. To investigate whether rivers are potential habitats or carriers for B. pseudomallei and to assess its geographical distribution in Laos, we studied 23 rivers including the Mekong, applying culture-based detection methods and PCR to water filters and streambed sediments. B. pseudomallei was present in 9% of the rivers in the dry season and in 57% in the rainy season. We found the pathogen exclusively in Southern and Central Laos, and mainly in turbid river water, while sediments were positive in 35% of the B. pseudomallei-positive sites. Our results provide evidence for a heterogeneous temporal and spatial distribution of B. pseudomallei in rivers in Laos with a clear north- south contrast. The seasonal dynamics and predominant occurrence of B. pseudomallei in particle-rich water suggest that this pathogen is washed out with eroded soil during periods of heavy rainfall and transported by rivers, while river sediments do not seem to be permanent habitats for B. pseudomallei. Rivers may thus be useful to assess the distribution and aquatic dispersal of B. pseudomallei and other environmental pathogens in their catchment area and beyond. Knowledge of the distribution and dispersal of pathogens in natural environments is crucial to understand the epidemiology of the diseases they cause, improve risk models and develop effective health management strate- 1,2 gies , particularly in countries with limited economic resources. Dispersal of microbes, including pathogenic species, is facilitated by transport in water and air, on particles or passive carriers (e.g. migrating birds) or in vectors and hosts . While most research on the fate and transport of water-borne pathogens focuses on enteric bacteria , studies addressing dispersal mechanisms of pathogens with environmental reservoirs, for example Burkholderia pseudomallei, are rare. The soil-dwelling bacterium B . pseudomallei is an emerging human path- ogen and causative agent of melioidosis, an underdiagnosed infectious disease with an estimated global inci- dence of 165,000 cases per year of whom approximately 50% die . Mainly known in Southeast Asia and Northern Australia, a recent environmental suitability model predicted a widespread occurrence of B. pseudomallei in tropical soils throughout the world. Consequently, melioidosis is probably endemic in many countries where it has never been reported . In soil, B. pseudomallei is spatially heterogeneously distributed across different scales, ranging from geographical regions to localised patches of a rice field , which makes its detection challenging. In addition to soil, B. pseudomallei has been found in a range of freshwater sources, including drinking water in 8 9–11 12,13 ai Th land and Australia and a river in Lao People’s Democratic Republic (Laos) , where the distribution of melioidosis remains uncertain. B. pseudomallei in freshwater bodies are potential sources of infection , particu- larly if they live permanently in these habitats. Moreover, rivers may transport B. pseudomallei from sources in the watershed and thereby indicate the presence of B. pseudomallei in the catchment and act as carriers for its environmental dispersal. Lao-Oxford-Mahosot Hospital-Wellcome Trust Research Unit, Microbiology Laboratory, Mahosot Hospital, 2 3 Vientiane, Laos. Department of Environmental Sciences, University of Basel, Basel, Switzerland. Swiss Tropical and Public Health Institute, University of Basel, Basel, Switzerland. GET, Université de Toulouse, IRD, CNRS, UPS, Toulouse, France. iEES-Paris (IRD, Sorbonne Universités, UPMC Univ Paris 06, CNRS, INRA, UPEC, 10 Université Paris Diderot), c/o Department of Agricultural Land Management (DALaM), Vientiane, Laos. Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK. Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, UK. Correspondence and requests for materials should be addressed to R.E.Z. (email: rosalie.zimmermann@unibas.ch) SCIENTIFIC REPo R ts | (2018) 8:8674 | DOI:10.1038/s41598-018-26684-y 1 www.nature.com/scientificreports/ Geographical coordinates B. pseudomallei River Tributary of Stations Region Latitude Longitude D R Mekong S. China Sea 6 N 19.95601 102.24113 − − N* 17.89870 101.62397 − − S* 17.97276 102.50410 − + S* 17.39714 104.79999 − + S* 16.00503 105.42449 − + S 15.10721 105.79878 − + Nam Ou Mekong 1 N 20.08642 102.26406 − − Nam Suang Nam Pa 1 N 19.97931 102.24728 − − Nam Pa Mekong 1 N 19.96049 102.28289 − − Nam Khan Mekong 1 N 19.78600 102.18311 − − Houay Khan Nam Khan 1 N 19.75995 102.18103 − − Houay Pano Nam Khan 3 N 19.86034 102.17262 − − N 19.85903 102.17061 − − N 19.85263 102.16901 − − Nam Lik Nam Ngum 1 N* 18.63280 102.28104 − − Nam Mi Mekong 1 N* 17.91917 101.68856 − − Nam Ngum Mekong 4 S* 18.52502 102.52631 − − S* 18.35581 102.57204 − + S* 18.20269 102.58588 − + S* 18.17879 103.05593 − + Nam Thon Mekong 1 S* 18.09152 102.28159 − + Nam Sang Mekong 1 S* 18.22284 102.14222 − + Nam Mang Mekong 1 S* 18.37019 103.19846 − + Nam Gniep Mekong 1 S* 18.41756 103.60217 − + Nam Xan Mekong 1 S* 18.39523 103.65408 − + Nam Kading Mekong 1 S* 18.32517 103.99924 − + Nam Hinboun Mekong 1 S* 17.72699 104.56798 − − Nam Xot Nam Theun 1(0) S* 17.93148 105.13257 − nd Mekong or Xe Nam Theun 1(0) S* 17.84229 105.05841 − nd Bangfai Xe Bangfai Mekong 3(1) S* 17.49436 105.42959 − nd S* 17.41563 105.20320 − nd S* 17.07782 104.98496 − + Xe Banghieng Mekong 1 S* 16.09804 105.37625 − + Xe Bangnouan Mekong 1 S 16.00290 105.47937 + + Xe Don Mekong 1 S 15.12390 105.80748 + + Table 1. Sampled rivers and stations in Laos. Stations: number of sampled stations in the dry season (rainy 38,39 season in brackets if different). Region: geographical classification based on ; stations marked * belong to the centre of Laos (reference: Department of Tourism Marketing, Ministry of Information, Laos). B. pseudomallei: presence of B. pseudomallei by at least one detection method in river water and/or sediment. N = north, S = south, D = dry season, R = rainy season, nd = no data. Flow direction depends on water level regulations of the Nam Theun dam lake. Geographical coordinates in degrees (WGS 1984) (dry season). The aims of this pilot study were to investigate (i) the geographical distribution of B . pseudomallei in Laos and (ii) whether rivers are potential reservoirs and/or carriers for B. pseudomallei. For this purpose, we used two independent methods, conventional culture and PCR aer enr ft ichment, to detect B . pseudomallei in river water and, for the first time, in streambed sediments, and assessed the distribution data in an environmental context to explain spatiotemporal variations. Results We investigated 23 rivers (36 sampling sites, hereaer s ft tations) in Laos between 15 °N and 20 °N, including the Mekong (Table 1). B. pseudomallei was present in 9% (2/23) of the rivers (2/36 stations) in the dry season. In contrast, we found the pathogen in 57% (12/21) of the rivers (17/31 stations) in the rainy season, detected on at least one water filter (pre- or main filter) by at least one detection method (conventional culture or PCR ae ft r enrichment; Table 1). Apart from one filter-negative, sediment-positive station in the dry season, we only found B. pseudomallei in the sediment when it was present in the water, i.e. in 35% (6/17) of the B. pseudomallei-positive stations in the rainy season. All B. pseudomallei-positive stations were situated in the centre and south of Laos, and B. pseudomallei-positive sediments were only detectable in the southern-most rivers (Fig. 1). The north-south SCIENTIFIC REPo R ts | (2018) 8:8674 | DOI:10.1038/s41598-018-26684-y 2 www.nature.com/scientificreports/ A Dry season B Rainy season Rivers n = 23 9% Rivers n = 21 43% 91% 57% pos. neg. neg. pos. B. pseudomallei in rivers in Laos B. p. China B. p.-positive sediments Myanmar B. p.-negative stations Laos Rivers Thailand North-south boundary 2817 m Cam- Vietnam 100 km bodia 70 m 100°E 102°E 104°E 106°E 100°E 102°E 104°E 106°E Figure 1. B. pseudomallei (B.p.)-positive and -negative stations and rivers in the dry season (A) and rainy 38,39 season. (B) North-south boundary based on , map background based on elevation data (U.S. Geological Survey, https://earthexplorer.usgs.gov; Central Intelligence Agency, https://www.cia.gov/library/publications/ the-world-factbook/index.html) and rivers/lakes/country shapefiles provided by the Centre for Development and Environment (CDE), CDE Lao Country Office, Laos. Geographic coordination system: WGS 1984, latitude and longitude in degrees; altitude of highest and lowest point in meters above mean sea level. Direct Post-enrichment Both methods B. pseudomallei positive units culture PCR positive Total Stations (only by respective method) 15 (3) 16 (4) 12 19 All samples 16 31 10 47 Pre-filters 3 12 1 15 Main filters 10 13 7 23 Stations with positive pre- and main filter 0 10 0 10 Sediment samples 3 6 2 9 Filter-positive, sediment-negative stations 11 10 7 11 Sediment-positive, filter-negative stations 2 1 0 3 Stations where all samples were positive 0 4 0 4 Table 2. Number of B. pseudomallei positive units comparing different detection methods and sample types (pre-filters, main filters, sediment). trend was also observable in B. pseudomallei-positive rivers with sampling sites in both regions, i.e. the Mekong (six sites) and Nam Ngum (four sites), where the northernmost 1–2 stations were negative and the 3–4 south- ernmost stations positive. The seasonal and regional contrast regarding the presence of B. pseudomallei was sta- tistically significant when comparing all stations or all rivers, as well as stations or rivers in the rainy season, and stations or rivers in the south (Fisher’s exact test, p ≤ 0.001). Almost as many B. pseudomallei-positive stations were identified by conventional culture as by molecular techniques (Table 2). However, PCR revealed a higher number of positive samples per station than culture, and the only two B. pseudomallei-positive stations in the dry season were detected by PCR. All culture-positive sed- iments resulted from direct incubation of the highest volume of sediment fluid (500 µ L) on Ashdown’s agar. B. pseudomallei-positive main filters (23/38) outnumbered pre-filters (15/38). The characteristics of physico-chemical water parameters measured on-site (turbidity, temperature, acidity, electrical conductivity as a proxy for salinity, dissolved oxygen, redox potential, altitude of the station) are shown in Table 3. Water temperature correlated moderately, and salinity, altitude, turbidity and pH weakly with the pres- ence of B. pseudomallei on water filters (undirectional correlation). However, all physico-chemical parameters were functions of season and/or of region and correlated with at least one other parameter (Table 3). For example, water temperature was higher in the rainy season and in the south, and correlated negatively with altitude, while salinity showed the opposite pattern. As a result, none of the parameters was a significant independent predictor SCIENTIFIC REPo R ts | (2018) 8:8674 | DOI:10.1038/s41598-018-26684-y 3 14°N 16°N 18°N 20°N 22°N www.nature.com/scientificreports/ Seasonal differences, Regional differences in mean (SD) rainy season, mean (SD) Corr. ratio Bravais-Pearson correlations Physico-chemical Dry Rainy parameters Median Min – Max season season North South B. p. Tur Temp pH EC DO ORP Altitude (m.a.s.l.) 175 74–513 322 (106) 140 (38)* 0.15* 0.01 −0.39* 0.02 0.52* −0.47* 0.33 Turbidity (NTU) 18 2–730 12 (11) 227 (218)* 257 (242) 206 (206) 0.13* 0.35* −0.21 −0.12 −0.07 −0.10 Temperature (°C) 26.5 19.5–30.0 25 (1.9) 27.6 (1.5)* 26.8 (1.8) 28.2 (1.1)* 0.29* −0.17 −0.10 −0.04 −0.23 Acidity (pH) 7.6 6.5–9.0 7.8 (0.5) 7.3 (0.4)* 7.4 (0.4) 7.3 (0.4) 0.09* 0.40* 0.34* 0.14 Electrical 152 10–623 194 (139) 152 (92)* 231 (80) 101 (58)* 0.15* −0.08 0.43* conductivity (µS/cm) Dissolved oxygen 85 25–138 92 (18) 73 (16)* 72 (17) 73 (16) 0.06 −0.05 (%) Redox potential 86 −39–275 118 (79) 85 (28) 75 (11) 92 (34) 0.00 (mV) Table 3. Characteristics of physico-chemical water parameters and altitude. Abbreviations: m.a.s.l. = meters above mean sea level, NTU = nephelometric turbidity units, mean = arithmetic mean, SD = standard deviation, Corr. ratio = correlation ratio, B. p. = B. pseudomallei, Tur = turbidity, Temp = temperature, pH = acidity, EC = electrical conductivity (proxy for salinity), DO = dissolved oxygen, ORP = redox potential. N = 67; exceptions: turbidity (n = 66), median, minimum and maximum of altitude in the rainy season (n = 31). e Th Bravais-Pearson correlation coefficient (r) is given for directional correlations between physico-chemical parameters, the correlation ratio (η ) for undirectional correlations between the presence of B. pseudomallei and physico-chemical parameters, range from 0 (no correlation) to 1 (perfect correlation). Statistical tests: seasonal comparison: paired t-test (n = 31 pairs, for turbidity n = 30 pairs), regional comparison: t-test, correlation ratio: t-test, Bravais-Pearson correlations: Pearson test; *statistically significant correlations or differences between groups, p < 0.01. of the presence of B. pseudomallei in multivariate logistic regression models restricted to conditions under which B. pseudomallei was most common (in the water of southern river stations in the rainy season). Discussion We detected B. pseudomallei in more than half (57%) of the investigated rivers, which indicates a widespread dis- tribution of the pathogen in Laos. To characterise rivers as potential reservoirs or carriers for B. pseudomallei, we analysed the seasonal dynamics of its occurrence in both river water and superficial near-riparian sediments. If rivers were reservoirs, i.e. permanent habitats for B. pseudomallei, we would expect to find the pathogen primarily and perennially in the uppermost streambed sediments which harbor the majority of bacterial biomass in rivers , and resuspended in the water column under conditions of increased turbulence, e.g. during floods. However, in accordance with the highest seasonal incidence of melioidosis , we detected B. pseudomallei predominantly in the rainy season while B. pseudomallei-positive sediments were rare and usually linked to B. pseudomallei-positive water samples. These findings suggest that rivers are potential carriers for B . pseudomallei, and streambed sed- iments do not seem to be permanent habitats for this bacterium although the occurrence of B. pseudomallei in deeper midstream sediments is unknown. Nevertheless, the role of rivers and other freshwater bodies in the seasonal transmission of melioidosis might be underestimated, despite the fact that melioidosis cases have rarely been associated with exposure to river water . e m Th ost likely source of B. pseudomallei in rivers are its known reservoir, tropical soils . Being present down to at least 90 cm depth , the pathogen is likely to be mobilised with eroded soil particles in surface and subsurface runoff and ultimately channeled into rivers. As suggested by B . pseudomallei-positive filters of different pore sizes, the pathogen may be transported free-floating or attached to suspended particles of various sizes. Under condi- tions of high discharge, B. pseudomallei may be washed onto the soil of flood plains or infiltrate alluvial banks and aquifers downriver and be washed away again, especially during periods of heavy rainfall. In the Mekong 20,21 basin, 90% of the annual precipitation (~1000 to 2800 mm) occurs during the southwest monsoon , when B. pseudomallei was most common. Rain and, consequently, runoff are the main erosional forces of climatic origin in humid tropical regions, and intensive rainfall has been associated with increased erosion and suspended sediment 22,23 load in the Mekong area . Accordingly, we detected B. pseudomallei predominantly in particle-rich water, as 10,12,13 observed in previous studies . However, B. pseudomallei was absent in the turbid rivers of the Northern Highlands, where sloping lands are 23,24 particularly susceptible to erosion due to extensive land-use changes . We can only speculate about the rea- sons why we detected the pathogen exclusively in the Mekong plain, although samples from melioidosis patients have been referred to the Mahosot Hospital Microbiology Laboratories from almost all Lao provinces (unpub- lished observations). Methodological considerations include the definition of the north-south boundary, which was based on limited sources, but classifying the southern-most northern stations as southern stations did not change the statistical significance of the north-south contrast regarding the presence of B . pseudomallei. Bias caused by non-random sampling (for reasons of accessibility) and bacterial loads below the detection limits of our methods cannot entirely be excluded. However, we applied two independent detection methods including post-enrichment PCR, which previously proved to be the most sensitive method for the detection of B. pseu- domallei in environmental samples . The absence or low numbers of B . pseudomallei may be a consequence of SCIENTIFIC REPo R ts | (2018) 8:8674 | DOI:10.1038/s41598-018-26684-y 4 www.nature.com/scientificreports/ contrasting climate, geological substrates, soil types, and land-use in the Northern Highlands compared to the Mekong plains in southern Laos. The higher proportion of irrigated rice cultivation (paddy rice) and industrial agricultural plantations in the Mekong plain in contrast to slash-and-burn cultivation in the north , for instance, as well as regionally distinctive parameters such as lower temperature or higher salinity values of northern river water (own data and ), might be aspects of a non-permissive environment for B. pseudomallei. However, direct conclusions cannot be drawn based on single water samples from rivers with large catchment areas, as B. pseu- domallei might originate from various sources upriver, having been associated with a broad range of soil types and 12,27–30 land-covers . For this reason, analyses of relationships between B. pseudomallei in rivers and environmental factors in a catchment area are considered to be most conclusive at the sub-catchment or meso-scale (10–100 2 12,31 km ) , and remain to be investigated in Laos and elsewhere. We provide evidence that rivers are potential carriers for B. pseudomallei, as has been shown for other soil organ- isms , but likely not permanent reservoirs for this pathogen. Rivers facilitate the dispersal of B. pseudomallei in the environment, possibly over long distances and to previously non-endemic areas. Thus, rivers are potential sentinels to explore the presence of B. pseudomallei in catchment areas, particularly during periods of intensive erosion and high discharge. Moreover, rivers may be useful to track potential sources and monitor the spatiotemporal dynamics of aquatic dispersal of B. pseudomallei and other environmental pathogens in a watershed and beyond. Methods Sample collection and processing. We investigated 36 stations at 23 perennial rivers, including the Mekong, in Laos between 15°N and 20°N in the dry (March) and rainy (July) seasons in 2016. The choice of rivers and sites was based on a broad geographical coverage of Laos and a range of differently sized direct or indirect tributaries to the Mekong. Several rivers were sampled at multiple sites along their course (Table 1). We collected unreplicated surface water samples from the riverside (near-riparian zone) using 1.5 L PET drinking water bot- tles (triple-rinsed with water from the sampling site), and from a mixed composite sample across the river at two southern Mekong stations. Wherever feasible, we collected bulk samples from the top 10 cm of near-riparian stre- ambed sediment using a 102 cm hand-held steel cylinder, and kept them in sterile, ziplocked plastic bags. On-site physico-chemical measurements included altitude and geographical coordinates using a GPS device (Garmin Oregon 650t), water turbidity using a nephelometric turbidity meter (Eutech TN100), and water temperature, acidity (pH), electrical conductivity (a proxy for salinity), dissolved oxygen, and redox potential using a portable multi-probe (YSI-556). All samples were transported in a cool box with ice packs. One to four days post-sam- pling, we manually homogenised the sediment samples and conducted vacuum filtration at the Mahosot Hospital Microbiology Laboratories with 500 mL (dry season) and 250 mL (rainy season) of water, using an electrical pump, 1-L glass flasks, a stainless-steel funnel (Whatman) and two membrane filters applied in succession: a pre-filter (5.0 µ m pore size) and a main filter (0.2 µ m pore size) (cellulose acetate, 47 mm diameter, Sartorius). The equipment was cleaned with 70% ethanol and sterile water between samples. Microbiological methods. To detect B. pseudomallei on water filters and in sediment, we applied two inde- pendent methods: conventional culture techniques and PCR after an enrichment step, a sensitive approach for the detection of B. pseudomallei in low-abundance environments . All microbiological analyses were conducted at the Mahosot Hospital Microbiology Laboratories in Class II Biosafety Cabinets. Culture. Water filters (one pre-filter and one main filter per sampling site) were placed surface-up on Ashdown’s agar while sediment samples were prepared as described previously for soil . In short, 100 g of homogenised sediment were mixed with 100 mL of sterile water in sterile, ziplocked plastic bags and left to settle at room temperature overnight before different volumes of supernatant (10, 100 and 500 µ L) were spread on Ashdown’s agar. In addition, 1 mL supernatant was enriched with 9 mL of selective TBSS-C50 at 40 °C for 48 h, and 10 µL of the enriched fluid incubated on Ashdown’s agar. All samples were incubated at 40 °C in air for up to 4 days with daily inspection (median 3 days, range 2–4 days). Suspect colonies were tested by agglutination with a latex reagent specific for the 200-kDa exopolysaccharide of B . pseudomallei resistance to colistimethate and sus- ceptibility to amoxicillin-clavulanic acid, and latex-positive isolates with these characteristics were confirmed by 36 37 API 20NE (BioMérieux, Basingstoke, UK) and a specific PCR based on with the following modifications: 20 µ L reaction mixture containing final concentrations of 0.5 µ M primers LPW13372 and LPW13373, 2 mM MgCl , 200 µ M each dNTP, 1 U Platinum Taq (Invitrogen) and 1x Platinum PCR buffer. Thermocycler conditions were 95 °C for 10 minutes, followed by 40 cycles of 95 °C for 30 seconds, 60 °C for 45 seconds and 72 °C for 60 seconds, and a final extension of 72 °C for 10 minutes. Pre-enrichment and DNA extraction. Pre-enrichment and DNA extraction were conducted as described previously with some modifications: Entire pre- and main filters and 20 g of homogenised sediment were immersed separately in 20 mL of modified Ashdown’s broth, and, after shaking the sediment samples at 12 × g for 2 h, vortexed and incubated at 37 °C in air for 42 h. e Th enriched samples were kept at −20 °C, defrosted and vortexed shortly before DNA extraction. Ae ft r settling for 20 min, the liquid phase of the enriched sediments was centrifuged at 700 × g for 2 min and mixed with 150 µ L of 3.5 mg/L aurintricarboxylic acid. Then, all enriched samples were centrifuged at 3220 × g for 45 min and DNA extracted from the sedimentation using the MoBio PowerSoil DNA isolation kit according to the manufacturer’s instructions with an additional cell lysis step (incu- bation with proteinase K at 55 °C for 30 min) . PCR. We applied a specific real-time PCR assay targeting a 115-base-pair region in the open-reading-frame 2 of the type III secretion system gene cluster (TTS1) of B. pseudomallei as described in with 500 nM SCIENTIFIC REPo R ts | (2018) 8:8674 | DOI:10.1038/s41598-018-26684-y 5 www.nature.com/scientificreports/ primers BpTT4176F and BpTT4290R, 250 nM probe BpTT4208P (Biosearch Technologies) and 1 U Platinum Taq (Invitrogen), using a Rotor-Gene 6000 system (Qiagen) with 45 amplification cycles. Two positive controls 3 4 (10 and 10 genome equivalents) and negative controls were included in every PCR run and showed the expected results. To control for PCR inhibition, 10 copies of Orientia tsutsugamushi 47-kDa plasmid was amplified with O. tsutsugamushi specific primers and probe . Inhibition was assumed to be absent if the spiked DNA amplified within ±2 Ct values from the positive inhibition controls which was the case for all samples (occasionally aer ft dilution). Mapping and statistics. Maps were created with ArcGIS 10.3 and Adobe Illustrator CS6 using GPS coor- dinates of the sampling sites, elevation data (U.S. Geological Survey, https://earthexplorer.usgs.gov; Central Intelligence Agency, https://www.cia.gov/library/publications/the-world-factbook/index.html) and rivers/lakes/ country shapefiles provided by the Centre for Development and Environment (CDE), CDE Lao Country Office. The geographical categories north (Northern Highlands) and south (Mekong plain and Annamite mountains, corresponding to the political centre and south) were based on a physio-geographical classification , a geological map and topographic features. Statistical analyses were computed with Stata 14 and R 3.4. Data availability. e Th datasets generated and analysed during the current study are available from the cor - responding author on reasonable request. References 1. Cho, K. H. et al. 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Rochelle- Newall, Prof M. Lehmann, Dr H. Niemann, Dr. T. Kuhn, J. Kobler-Waldis, and R. Strunk for their help with laboratory work, technical inputs or logistical support, to V. Roth and the Centre for Development and Environment for providing map shapefiles, and to the Nam Theun 2 Power Company (NTPC) for providing logistical support and access to their site. This study was funded by the US Defence Threat Reduction Agency Cooperative Biological Engagement Programme (contract HDTRA-16-C-0017) (main funding), the Lao-Oxford- Mahosot Hospital-Wellcome Trust Research Unit funded by the Wellcome Trust of Great Britain (Grant number 089275/H/09/Z), the French National Research Agency (TecItEasy project, ANR-13-AGRO-0007), and the Institut de Recherche pour le Développement. Author Contributions R.E.Z., D.A.B.D., O.R., A.P., J.Z. and P.N.N. conceived and designed the study, R.E.Z., O.R., A.P. and S.R. undertook the e fi ldwork, R.E.Z., V.D., M.T.R. and D.A.B.D. conducted and supervised laboratory analyses, R.E.Z. and Y.A. conducted statistical analyses, R.E.Z. wrote the manuscript, and all authors reviewed and approved the manuscript. Additional Information Competing Interests: The authors declare no competing interests. Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Cre- ative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not per- mitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. © The Author(s) 2018 SCIENTIFIC REPo R ts | (2018) 8:8674 | DOI:10.1038/s41598-018-26684-y 7
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Published: Jun 6, 2018