Benchmarking microbiome transformations favors experimental quantitative approaches to address compositionality and sampling depth biases

While metagenomic sequencing has become the tool of preference to study host-associated microbial communities, downstream analyses and clinical interpretation of microbiome data remains challenging due to the sparsity and compositionality of sequence matrices. Here, we evaluate both computational and experimental approaches proposed to mitigate the impact of these outstanding issues. Generating fecal metagenomes drawn from simulated microbial communities, we benchmark the performance of thirteen commonly used analytical approaches in terms of diversity estimation, identification of taxon-taxon associations, and assessment of taxon-metadata correlations under the challenge of varying microbial ecosystem loads. We find quantitative approaches including experimental procedures to incorporate microbial load variation in downstream analyses to perform significantly better than computational strategies designed to mitigate data compositionality and sparsity, not only improving the identification of true positive associations, but also reducing false positive detection. When analyzing simulated scenarios of low microbial load dysbiosis as observed in inflammatory pathologies, quantitative methods correcting for sampling depth show higher precision compared to uncorrected scaling. Overall, our findings advocate for a wider adoption of experimental quantitative approaches in microbiome research, yet also suggest preferred transformations for specific cases where determination of microbial load of samples is not feasible.

Combined Pulsed RF GD-OES and HAXPES for Quantified Depth Profiling through Coatings

Chemical characterization at buried interfaces is a real challenge, as the physico-chemical processes operating at the interface govern the properties of many systems and devices. We have developed a methodology based on the combined use of pulsed RF GD-OES (pulsed Radio Frequency Glow Discharge Optical Emission Spectrometry) and XPS (X-ray Photoelectron Spectroscopy) to facilitate the access to deeply buried locations (taking advantage of the high profiling rate of the GD-OES) and perform an accurate chemical diagnosis using XPS directly inside the GD crater. The reliability of the chemical information is, however, influenced by a perturbed layer present at the surface of the crater, hindering traditional XPS examination due to a relatively short sampling depth. Sampling below the perturbed layer may, however, can be achieved using a higher energy excitation source with an increased sampling depth, and is enabled here by a new laboratory-based HAXPES (Hard X-ray PhotoElectron Spectroscopy) (Ga-Kα, 9.25 keV). This new approach combining HAXPES with pulsed RF GD-OES requires benchmarking and is here demonstrated and evaluated on InP. The perturbed depth is estimated and the consistency of the chemical information measured is demonstrated, offering a new route for advanced chemical depth profiling through coatings and heterostructures.

Sampling bias minimization in disease frequency estimates

An accurate estimate of the number of infected individuals in any disease is crucial. Current estimates are mainly based on the fraction of positive samples or the total number of positive samples. However, both methods are biased and sensitive to the sampling depth. We here propose an alternative method to use the attributes of each sample to estimate the change in the total number of positive patients in the total population. We present a Bayesian estimator assuming a combination of condition and time-dependent probability of being positive, and mixed implicit-explicit solution for the probability of a person with conditions i at time t of being positive. We use this estimate to predict the total probability of being positive at a given day t. We show that these estimate results are smooth and not sensitive to the properties of the samples. Moreover, these results are a better predictor of future mortality.

Impact of sampling depth on pathogen detection in pit latrines

Wastewater based epidemiology (WBE) is increasingly used to provide decision makers with actionable data about community health. WBE efforts to date have primarily focused on sewer-transported wastewater in high-income countries, but at least 1.8 billion people in low- and middle-income countries (LMIC) use onsite sanitation systems such as pit latrines and septic tanks. Like wastewater, fecal sludges from such systems offer similar advantages in community pathogen monitoring and other epidemiological applications. To evaluate the distribution of enteric pathogens inside pit latrines–which could inform sampling methods for WBE in LMIC settings unserved by sewers–we collected fecal sludges from the surface, mid-point, and maximum-depth of 33 pit latrines in urban and peri-urban Malawi and analyzed the 99 samples for 20 common enteric pathogens via multiplex quantitative reverse transcription PCR. Using logistic regression adjusted for household population, latrine sharing, the presence of a concrete floor or slab, water source, and anal cleansing materials, we found no significant difference in the odds of detecting the 20 pathogens from the mid-point (adjusted odds ratio, aOR = 1.1; 95% confidence interval = 0.73, 1.6) and surface samples (aOR = 0.80, 95% CI = 0.54, 1.2) compared with those samples taken from the maximum depth. Our results suggest that, for the purposes of routine pathogen monitoring, pit latrine sampling depth does not strongly influence the odds of detecting enteric pathogens by molecular methods. A single sample from the pit latrines’ surface, or a composite of surface samples, may be preferred as the most recent material contributed to the pit and may be easiest to collect.

Content of heavy metals in the bottom sediments of the wastewater of the processing enterprise

Wastewater contains stable and unstable pollutants. In the process of self-cleaning, a large amount of bottom sediments accumulates, especially in artificially created storage ponds. As a result of the increasing load on this type of water bodies and the accumulation of bottom sediments, the self-purification ability is sharply reduced, which entails an additional load on the environment. The use of bottom sediments for biological reclamation is allowed after the establishment of the hazard class in accordance with the current regulatory documents and taking measures to neutralize them. The purpose of this separate fragment of work was to study the total content of heavy metals in the bottom sediments of storage ponds of a milk processing enterprise and determine the possibility of their further use. As a result of the data obtained, it can be concluded that the lead content was 14.6-17.3 mg/kg, depending on the depth of the bottom sediment sampling layer. At a sampling depth of 0.5-1.0 meters, the lead content was maximum and exceeded the clarke values of the element by 8.1%. There is a 2 time excess of the clarke values for cadmium at a depth of 1.0-1.5 meters. Indicators for zinc and copper were 12.4-14.1 mg/kg and 5.9-9.8 mg/kg, respectively, and did not go beyond the threshold limits of the compared values. The research results allow concluding that the bottom sediments of the storage ponds of the milk processing enterprise are not toxic. Therefore, they can be used in the composition of soil.

Determination of stress-strain properties of thawing soils in oedometer

Article presents relation of thawing coefficient (Ath) and compressibility coefficient during thawing (m) to the sampling depth and physical state of frozen soils in loams, typical for the Arctic region of the European part of Russia. Conclusions are drawn that help to predict thawing deformation of the tested soils according to their physical characteristics.

Stratified Soil Sampling Improves Predictions of P Concentration in Surface Runoff and Tile Discharge

Phosphorus (P) stratification in agricultural soils has been proposed to increase the risk of P loss to surface waters. Stratified soil sampling that assesses soil test P (STP) in a shallow soil horizon may improve predictions of P concentrations in surface and subsurface discharge compared to single depth agronomic soil sampling. However, the utility of stratified sampling efforts for enhancing understanding of environmental P losses remains uncertain. In this study, we examined the potential benefit of integrating stratified sampling into existing agronomic soil testing efforts for predicting P concentrations in discharge from 39 crop fields in NW Ohio, USA. Edge-of-field (EoF) dissolved reactive P (DRP) and total P (TP) flow-weighted mean concentrations in surface runoff and tile drainage were positively related to soil test P (STP) measured in both the agronomic sampling depth (0–20 cm) and shallow sampling depth (0–5 cm). Tile and surface DRP and TP were more closely related to shallow depth STP than agronomic STP, as indicated by regression models with greater coefficients of determination (R2) and lesser root-mean square errors (RMSE). A multiple regression model including the agronomic STP and P stratification ratio (Pstrat) provided the best model fit for DRP in surface runoff and tile drainage and TP in tile drainage. Additionally, STP often varied significantly between soil sampling events at individual sites and these differences were only partially explained by management practices, highlighting the challenge of assessing STP at the field scale. Overall, the linkages between shallow STP and P transport persisted over time across agricultural fields and incorporating stratified soil sampling approaches showed potential for improving predictions of P concentrations in surface runoff and tile drainage.

Spatial structure of the pink shrimp Penaeus (Farfantepenaeus) notialis (Pérez Farfante, 1967) (Decapoda, Penaeidae) in the Colombian Caribbean: implications for fisheries management

The objective of this study was to assess the patterns in the spatial distribution, size structure, morphometric relationships, and relationships of biomass and size to sampling depth and distance to the coast of Penaeus notialis in the Colombian Caribbean. The biological data were collected on board a shrimp trawler. The females were larger and heavier than the males, which indicated distinct sexual dimorphism in body size. The cephalothorax length at 50% maturity in females was 26.49 mm, and in males, it was 15.13 mm. Relatively high biomass values were found in the southern zone of the study area at depths between 25.6 and 49.3 m and between 3.94 and 7.80 nmi (= 7.29-14.45 km) from the coast. We found a clear spatial structure of biomass and size in relation to depth, so that the fishing effort can be directed to the locations of the adult population.