Potential mechanisms for achieving agricultural benefits from biochar application to temperate soils: a review

Natural organic biomass burning creates black carbon which forms a considerable proportion of the soil’s organic carbon. Due to black carbon’s aromatic structure it is recalcitrant and has the potential for long-term carbon sequestration in soil. Soils within the Amazon-basin contain numerous sites where the ‘dark earth of the Indians’ (Terra preta de Indio, or Amazonian Dark Earths (ADE)) exist and are composed of variable quantities of highly stable organic black carbon waste (‘biochar’). The apparent high agronomic fertility of these sites, relative to tropical soils in general, has attracted interest. Biochars can be produced by ‘baking’ organic matter under low oxygen (‘pyrolysis’). The quantities of key mineral elements within these biochars can be directly related to the levels of these components in the feedstock prior to burning. Their incorporation in soils influences soil structure, texture, porosity, particle size distribution and density. The molecular structure of biochars shows a high degree of chemical and microbial stability. A key physical feature of most biochars is their highly porous structure and large surface area. This structure can provide refugia for beneficial soil micro-organisms such as mycorrhizae and bacteria, and influences the binding of important nutritive cations and anions. This binding can enhance the availability of macro-nutrients such as N and P. Other biochar soil changes include alkalisation of soil pH and increases in electrical conductivity (EC) and cation exchange capacity (CEC). Ammonium leaching has been shown to be reduced, along with N₂O soil emissions. There may also be reductions in soil mechanical impedance. Terra preta soils contain a higher number of ‘operational taxonomic units’ and have highly distinctive microbial communities relative to neighbouring soils. The potential importance of biochar soil incorporation on mycorrhizal fungi has also been noted with biochar providing a physical niche devoid of fungal grazers. Improvements in soil field capacity have been recorded upon biochar additions. Evidence shows that bioavailability and plant uptake of key nutrients increases in response to biochar application, particularly when in the presence of added nutrients. Depending on the quantity of biochar added to soil significant improvements in plant productivity have been achieved, but these reports derive predominantly from studies in the tropics. As yet there is limited critical analysis of possible agricultural impacts of biochar application in temperate regions, nor on the likelihood of utilising such soils as long-term sites for carbon sequestration. This review aims to determine the extent to which inferences of experience mostly from tropical regions could be extrapolated to temperate soils and to suggest areas requiring study.     

Aptamer-based multiplexed proteomic technology for biomarker discovery

Background

The interrogation of proteomes (“proteomics”) in a highly multiplexed and efficient manner remains a coveted and challenging goal in biology and medicine.

Methodology/Principal Findings

We present a new aptamer-based proteomic technology for biomarker discovery capable of simultaneously measuring thousands of proteins from small sample volumes (15 µL of serum or plasma). Our current assay measures 813 proteins with low limits of detection (1 pM median), 7 logs of overall dynamic range (∼100 fM–1 µM), and 5% median coefficient of variation. This technology is enabled by a new generation of aptamers that contain chemically modified nucleotides, which greatly expand the physicochemical diversity of the large randomized nucleic acid libraries from which the aptamers are selected. Proteins in complex matrices such as plasma are measured with a process that transforms a signature of protein concentrations into a corresponding signature of DNA aptamer concentrations, which is quantified on a DNA microarray. Our assay takes advantage of the dual nature of aptamers as both folded protein-binding entities with defined shapes and unique nucleotide sequences recognizable by specific hybridization probes. To demonstrate the utility of our proteomics biomarker discovery technology, we applied it to a clinical study of chronic kidney disease (CKD). We identified two well known CKD biomarkers as well as an additional 58 potential CKD biomarkers. These results demonstrate the potential utility of our technology to rapidly discover unique protein signatures characteristic of various disease states.

Conclusions/Significance

We describe a versatile and powerful tool that allows large-scale comparison of proteome profiles among discrete populations. This unbiased and highly multiplexed search engine will enable the discovery of novel biomarkers in a manner that is unencumbered by our incomplete knowledge of biology, thereby helping to advance the next generation of evidence-based medicine.     

DNA‐PK suppresses a p53‐independent apoptotic response to DNA damage

p53 is required for DNA damage‐induced apoptosis, which is central to its function as a tumour suppressor. Here, we show that the apoptotic defect of p53‐deficient cells is nearly completely rescued by inactivation of any of the three subunits of the DNA repair holoenzyme DNA‐dependent protein kinase (DNA‐PK). Intestinal crypt cells from p53 nullizygous mice were resistant to radiation‐induced apoptosis, whereas apoptosis in DNA‐PK_cs/p53, Ku80/p53 and Ku70/p53 double‐null mice was quantitatively equivalent to that seen in wild‐type mice. This p53‐independent apoptotic response was specific to the loss of DNA‐PK, as it was not seen in ligase IV (Lig4)/p53 or ataxia telangiectasia mutated (Atm)/p53 double‐null mice. Furthermore, it was associated with an increase in phospho‐checkpoint kinase 2 (CHK2), and cleaved caspases 3 and 9, the latter indicating engagement of the intrinsic apoptotic pathway. This shows that there are two separate, but equally effective, apoptotic responses to DNA damage: one is p53 dependent and the other, engaged in the absence of DNA‐PK, does not require p53.     

Computational and analytical framework for small RNA profiling by high-throughput sequencing

The advent of high-throughput sequencing (HTS) methods has enabled direct approaches to quantitatively profile small RNA populations. However, these methods have been limited by several factors, including representational artifacts and lack of established statistical methods of analysis. Furthermore, massive HTS data sets present new problems related to data processing and mapping to a reference genome. Here, we show that cluster-based sequencing-by-synthesis technology is highly reproducible as a quantitative profiling tool for several classes of small RNA from Arabidopsis thaliana. We introduce the use of synthetic RNA oligoribonucleotide standards to facilitate objective normalization between HTS data sets, and adapt microarray-type methods for statistical analysis of multiple samples. These methods were tested successfully using mutants with small RNA biogenesis (miRNA-defective dcl1 mutant and siRNA-defective dcl2 dcl3 dcl4 triple mutant) or effector protein (ago1 mutant) deficiencies. Computational methods were also developed to rapidly and accurately parse, quantify, and map small RNA data.     

Linkage disequilibrium network analysis (LDna) gives a global view of chromosomal inversions,local adaptation and geographic structure

Recent advances in sequencing allow population‐genomic data to be generated for virtually any species. However, approaches to analyse such data lag behind the ability to generate it, particularly in nonmodel species. Linkage disequilibrium (LD, the nonrandom association of alleles from different loci) is a highly sensitive indicator of many evolutionary phenomena including chromosomal inversions, local adaptation and geographical structure. Here, we present linkage disequilibrium network analysis (LDna), which accesses information on LD shared between multiple loci genomewide. In LD networks, vertices represent loci, and connections between vertices represent the LD between them. We analysed such networks in two test cases: a new restriction‐site‐associated DNA sequence (RAD‐seq) data set for Anopheles baimaii, a Southeast Asian malaria vector; and a well‐characterized single nucleotide polymorphism (SNP) data set from 21 three‐spined stickleback individuals. In each case, we readily identified five distinct LD network clusters (single‐outlier clusters, SOCs), each comprising many loci connected by high LD. In A. baimaii, further population‐genetic analyses supported the inference that each SOC corresponds to a large inversion, consistent with previous cytological studies. For sticklebacks, we inferred that each SOC was associated with a distinct evolutionary phenomenon: two chromosomal inversions, local adaptation, population‐demographic history and geographic structure. LDna is thus a useful exploratory tool, able to give a global overview of LD associated with diverse evolutionary phenomena and identify loci potentially involved. LDna does not require a linkage map or reference genome, so it is applicable to any population‐genomic data set, making it especially valuable for nonmodel species.     

Potent Dengue Virus Neutralization by a Therapeutic Antibody with Low Monovalent Affinity Requires Bivalent Engagement

We recently described our most potently neutralizing monoclonal antibody, E106, which protected against lethal Dengue virus type 1 (DENV-1) infection in mice. To further understand its functional properties, we determined the crystal structure of E106 Fab in complex with domain III (DIII) of DENV-1 envelope (E) protein to 2.45 Å resolution. Analysis of the complex revealed a small antibody-antigen interface with the epitope on DIII composed of nine residues along the lateral ridge and A-strand regions. Despite strong virus neutralizing activity of E106 IgG at picomolar concentrations, E106 Fab exhibited a ∼20,000-fold decrease in virus neutralization and bound isolated DIII, E, or viral particles with only a micromolar monovalent affinity. In comparison, E106 IgG bound DENV-1 virions with nanomolar avidity. The E106 epitope appears readily accessible on virions, as neutralization was largely temperature-independent. Collectively, our data suggest that E106 neutralizes DENV-1 infection through bivalent engagement of adjacent DIII subunits on a single virion. The isolation of anti-flavivirus antibodies that require bivalent binding to inhibit infection efficiently may be a rare event due to the unique icosahedral arrangement of envelope proteins on the virion surface.     

Metabolomic Derangements Are Associated with Mortality in Critically Ill Adult Patients

Objective

To identify metabolomic biomarkers predictive of Intensive Care Unit (ICU) mortality in adults.

Rationale

Comprehensive metabolomic profiling of plasma at ICU admission to identify biomarkers associated with mortality has recently become feasible.

Methods

We performed metabolomic profiling of plasma from 90 ICU subjects enrolled in the BWH Registry of Critical Illness (RoCI). We tested individual metabolites and a Bayesian Network of metabolites for association with 28-day mortality, using logistic regression in R, and the CGBayesNets Package in MATLAB. Both individual metabolites and the network were tested for replication in an independent cohort of 149 adults enrolled in the Community Acquired Pneumonia and Sepsis Outcome Diagnostics (CAPSOD) study.

Results

We tested variable metabolites for association with 28-day mortality. In RoCI, nearly one third of metabolites differed among ICU survivors versus those who died by day 28 (N = 57 metabolites, p<.05). Associations with 28-day mortality replicated for 31 of these metabolites (with p<.05) in the CAPSOD population. Replicating metabolites included lipids (N = 14), amino acids or amino acid breakdown products (N = 12), carbohydrates (N = 1), nucleotides (N = 3), and 1 peptide. Among 31 replicated metabolites, 25 were higher in subjects who progressed to die; all 6 metabolites that are lower in those who die are lipids. We used Bayesian modeling to form a metabolomic network of 7 metabolites associated with death (gamma-glutamylphenylalanine, gamma-glutamyltyrosine, 1-arachidonoylGPC(20:4), taurochenodeoxycholate, 3-(4-hydroxyphenyl) lactate, sucrose, kynurenine). This network achieved a 91% AUC predicting 28-day mortality in RoCI, and 74% of the AUC in CAPSOD (p<.001 in both populations).

Conclusion

Both individual metabolites and a metabolomic network were associated with 28-day mortality in two independent cohorts. Metabolomic profiling represents a valuable new approach for identifying novel biomarkers in critically ill patients.     

Experimental selection of long‐term intracellular mycobacteria

Some intracellular bacteria are known to cause long‐term infections that last decades without compromising the viability of the host. Although of critical importance, the adaptations that intracellular bacteria undergo during this long process of residence in a host cell environment remain obscure. Here, we report a novel experimental approach to study the adaptations of mycobacteria imposed by a long‐term intracellular lifestyle. Selected Mycobacterium bovis BCG through continuous culture in macrophages underwent an adaptation process leading to impaired phenolic glycolipids (PGL) synthesis, improved usage of glucose as a carbon source and accumulation of neutral lipids. These changes correlated with increased survival of mycobacteria in macrophages and mice during re‐infection and also with the specific expression of stress‐ and survival‐related genes. Our findings identify bacterial traits implicated in the establishment of long‐term cellular infections and represent a tool for understanding the physiological states and the environment that bacteria face living in fluctuating intracellular environments.