Molecular signatures of soil-derived dissolved organic matter constrained by mineral weathering

Dissolved organic matter(DOM)in soils drives biogeochemical cycling and soil functions in different directions depending on its molecular signature.Notably,there is a distinct paucity of information concerning how the molecular signatures of soil DOM vary with different degrees of weathering across wide geographic scales.Herein,we resolved the DOM molecular signatures from 22 diverse Chinese reference soils and linked them with soil organic matter and weathering-related mineralogical properties.The mixed-effects models revealed that the yields of DOM were determined by soil organic carbon content,whereas the molecular signature of DOM was primarily constrained by the weathering-related dimension.The soil weathering index showed a positive effect on the lability and a negative effect on the aromaticity of DOM.Specifically,DOM in highly weathered acidic soils featured more amino sugars,carbohydrates,and aliphatics,as well as less O-rich polyphenols and condensed aromatics,thereby conferring a higher DOM biolability and lower DOM aromaticity.This study highlights the dominance of the weathering-related dimension in constraining the molecular signatures and potential functions of DOM in soils across a wide geographic scale.

Denoising Autoencoder, A Deep Learning Algorithm, Aids the Identification of A Novel Molecular Signature of Lung Adenocarcinoma

Precise biomarker development is a key step in disease management. However, most of the published biomarkers were derived from a relatively small number of samples with supervised approaches. Recent advances in unsupervised machine learning promise to leverage very large datasets for making better predictions of disease biomarkers. Denoising autoencoder(DA) is one of the unsupervised deep learning algorithms, which is a stochastic version of autoencoder techniques. The principle of DA is to force the hidden layer of autoencoder to capture more robust features by reconstructing a clean input from a corrupted one. Here, a DA model was applied to analyze integrated transcriptomic data from 13 published lung cancer studies, which consisted of 1916 human lung tissue samples. Using DA, we discovered a molecular signature composed of multiple genes for lung adenocarcinoma(ADC). In independent validation cohorts, the proposed molecular signature is proved to be an effective classifier for lung cancer histological subtypes. Also, this signature successfully predicts clinical outcome in lung ADC, which is independent of traditional prognostic factors. More importantly, this signature exhibits a superior prognostic power compared with the other published prognostic genes. Our study suggests that unsupervised learning is helpful for biomarker development in the era of precision medicine.

Design of bio-oil additives via molecular signature descriptors using a multi-stage computer-aided molecular design framework

Direct application of bio-oil from fast pyrolysis as a fuel has remained a challenge due to its undesirable attributes such as low heating value,high viscosity,high corrosiveness and storage instability.Solvent addition is a simple method for circumventing these disadvantages to allow further processing and storage.In this work,computer-aided molecular design tools were developed to design optimal solvents to upgrade bio-oil whilst having low environmental impact.Firstly,target solvent requirements were translated into measurable physical properties.As different property prediction models consist different levels of structural information,molecular signature descriptor was used as a common platform to formulate the design problem.Because of the differences in the required structural information of different property prediction models,signatures of different heights were needed in formulating the design problem.Due to the combinatorial nature of higher-order signatures,the complexity of a computer-aided molecular design problem increases with the height of signatures.Thus,a multi-stage framework was developed by developing consistency rules that restrict the number of higher-order signatures.Finally,phase stability analysis was conducted to evaluate the stability of the solvent-oil blend.As a result,optimal solvents that improve the solvent-oil blend properties while displaying low environmental impact were identified.

Molecular signature of soil organic matter under different land uses in the Lake Chaohu Basin

The concentration and molecular composition of soil organic matter(SOM)are important factors in mitigation against climate change as well as providing other ecosystem services.Our quantitative understanding of how land use influences SOM molecular composition and associated turnover dynamics is limited,which underscores the need for high-throughput analytical approaches and molecular marker signatures to clarify this etiology.Combining a high-throughput untargeted mass spectrometry screening and molecular markers,we show that forest,farmland and urban land uses result in distinct molecular signatures of SOM in the Lake Chaohu Basin.Molecular markers indicate that forest SOM has abundant carbon contents from vegetation and condensed organic carbon,leading to high soil organic carbon(SOC)concentration.Farmland SOM has moderate carbon contents from vegetation,and limited content of condensed organic carbon,with SOC significantly lower than that of forest soils.Urban SOM has high abundance of condensed organic carbon markers due to anthropogenic activities but relatively low in markers from vegetation.Consistently,urban soils have the highest black carbon/SOC ratio among these land uses.Overall,our results suggested that the molecular signature of SOM varies significantly with land use in the Lake Chaohu Basin,influencing carbon dynamics.Our strategy of molecular fingerprinting and marker discovery is expected to enlighten further research on SOM molecular signatures and cycling dynamics.

Molecular Determinants of Prognosis in Hepatocellular Carcinoma

Hepatocellular carcinoma is one of the leading causes of death by cancer worldwide.Prognosis of hepatocellular carcinoma is determined by characteristics of the tumor and the surrounding cirrhotic liver.Several molecular signatures reflecting tumor biology and derived from tumor analyses predict early tumor recurrence and survival.In contrast,molecular signatures from cirrhotic non-tumor samples are enriched in immunity/inflammation related genes and could predict late tumor recurrence.Moreover,combination of clinical,pathological,and molecular features may refine prognosis prediction in these patients.Finally,molecular signatures from both tumor and non-tumor tissues will be helpful in the future to guide treatments in different clinical settings.

Chemodiversity of soil dissolved organic matter affected by contrasting microplastics from different types of polymers

Chemodiversity of dissolved organic matter(DOM)is a crucial factor controlling soil nutrient availability,greenhouse gas emissions,and pollutant migration.Microplastics(MPs)are widespread pollutants in terrestrial ecosystems in many regions.However,the effects of MPs on DOM chemodiversity are not sufficiently understood,particularly under different types of polymers.Using UV-Vis spectroscopy,3D fluorescence spectroscopy,and Fourier-transform ion cyclotron resonance mass spectrometry,the effects of three prevalent MPs[polyethylene,polystyrene,and polyvinyl chloride(PVC)]on the chemical properties and composition of soil DOM were investigated via a 310-d soil incubation experiment.The results showed that MPs reduced the aromatic and hydrophobic soil DOM components by more than 20%,with PVC MPs having the greatest effect.Furthermore,as MP contents increase,the humification level of soil DOM significantly decreases.MPs increased DOM molecules with no heteroatom by 8.3%-14.0%,but decreased DOM molecules with nitrogen content by 17.0%-47.8%.This may be because MPs cause positive“priming effect,”resulting in the breakdown of bioavailable components in soil DOM.This is also related to MPs changing microbial richness and diversity and enriching microbial communities involved in lignin compositions degradation.In the presence of MPs,soil DOM chemodiversity depended on soil pH,electrical conductivity,dissolved organic carbon,soil organic matter,bacterial Shannon,and fungal Chao index.Specifically,DOM in MP-contaminated soils featured more lipids and less condensed aromatics and proteins/amino sugars,thereby conferring a lower DOM aromaticity and higher lability.

Diversity of nivicolous myxomycetes of the Teberda State Biosphere Reserve (Northwestern Caucasus,Russia)

Nivicolous myxomycete assemblages were surveyed on the northwest of the Greater Caucasian ridge in May-June 2010 and 2011 at a north facing transect between 1,700 and 2,920 m elevation of the summit Malaya Khatipara situated within the Teberda State Biosphere Reserve.Morphological characters of 396 collections representing 45 taxa(39 species,3 varieties,and 3 forms)of myxomycetes in 8 genera and 5 families were recorded.Many(13)taxa are classified as rare(a species represents<0.5%of all records).Only seven species were found to be widely distributed(present in 50%or more of the 17 studied localities).To confirm the assignment of specimens to morphospecies,we obtained independently from determination 145 partial sequences of the 18S SSU rRNA gene from 35 taxa of Lamproderma,Meriderma,Physarum and Diderma,which turned out to represent 58 genotypes.Most of the taxa represented by more than one sequence had several genotypes,with an average of 1.7 genotypes per taxon.Except for three taxonomically difficult groups of species,partial SSU sequences did well correspond with the respective morphospecies and where similar or identical to sequences of specimens from the European Alps,making this marker a good candidate for barcoding in myxomycetes.Species richness and diversity increased from subalpine crooked-stem birch forests(23 species,2 varieties,H′02.8,E00.88,D00.08)to alpine dwarf shrub communities(34 species and 2 varieties,2 forms,H′03.2,E00.89,D00.05)but decreased again for alpine meadows(27 species and 2 varieties,2 forms,H′03.1,E00.91,D00.06).Species richness and alpha-diversity reached maximum values for ground litter,whereas leaves and stems of living shrubs above ground harboured a more depauperate myxomycete assemblage.