Integrating intracellular and extracellular proteomic profiling for in-depth investigations of cellular communication in a model of prostate cancer

Cellular communication is essential for cell-cell interactions, maintaining homeostasis and progression of certain disease states. While many studies examine extracellular proteins, the holistic extracellular proteome is often left uncaptured, leaving gaps in our understanding of how all extracellular proteins may impact communication and interaction. We used a cellular-based proteomics approach to more holistically profile both the intracellular and extracellular proteome of prostate cancer. Our workflow was generated in such a manner that multiple experimental conditions can be observed with the opportunity for high throughput integration. Additionally, this workflow is not limited to a proteomic aspect, as metabolomic and lipidomic studies can be integrated for a multi-omics workflow. Our analysis showed coverage of over 8000 proteins while also garnering insights into cellular communication in the context of prostate cancer development and progression. Identified proteins covered a variety of cellular processes and pathways, allowing for the investigation of multiple aspects into cellular biology. This workflow demonstrates advantages for integrating intra- and extracellular proteomic analyses as well as potential for multi-omics researchers. This approach possesses great value for future investigations into the systems biology aspects of disease development and progression.     

Modelling of mouse experimental colitis by global property screens: a holistic approach to assess drug effects in inflammatory bowel disease

Preclinical disease models play an important role in the establishment of new treatment paradigms, identification of biomarkers and assessment of drug efficacy and safety. However, the accuracy of these models in context of the human disease are sometimes questioned, e.g. due to trials failing to confirm efficacy in humans. We suggest that one reason behind this gap in predictability may relate to how the preclinical data is analyzed and interpreted. In the present paper, we introduce a holistic approach to analyze and illustrate data in context of one of the most commonly used colitis models, i.e. the mouse dextran sulphate sodium (DSS) colitis model. Diseased mice were followed over time along disease progression and by use of tool pharmacological compounds activating nuclear hormone receptors, respectively. A new multivariate statistics approach was applied including principal component analysis (PCA) with treatment prediction subsequent to establishing the principal component analysis model. Thus, several studies could be overlaid and compared to each other in a new, comprehensive and holistic way. This method, named mouse colitis global property screening, appears applicable not only to any animal modelling series of studies but also to human clinical studies. The prerequisites for the study set up and calculations are delineated and examples of new learnings from the global property screening will be presented.     

Estimating red deer (<Emphasis Type="Italic">Cervus elaphus</Emphasis>) population size in the Southern Black Forest: the role of hunting in population control

Numerous studies have addressed the question of whether hunting is capable of limiting the abundance of ungulates in the northern hemisphere. We investigated whether the hunting of red deer (Cervus elaphus) has reduced their abundance in the Southern Black Forest (area 17,500 ha), Southern Germany, since 2006. Red deer abundance was estimated using data obtained from visual counts at winter feeding sites, track counts, and bag records. An age- and sex-structured population model to estimate the winter population size was also constructed using bag records. The estimated red deer population size was evaluated according to a non-invasive genetic mark-recapture approach. The results showed that the hunting of red deer can reduce their population size if the hunting regime is part of a holistic management concept that takes into account the uncertainty of population size estimates and is implemented at scales appropriate to the management of this species.     

Evaluating ecosystem-based natural disaster management

Abstract

Not many rigorous researches have studied on how ecosystems have interacted with the occurrence of natural disaster. This article aims to evaluate the role of ecosystems in the field of natural disaster management with the ultimate goal of reducing its various impacts. Qualitative content analysis has been utilized as the principal methodology. Additionally, the ecosystem low-awareness approach has been compared with the ecosystem integration approach with respect to international institutions, national governments, business corporations, non-government organizations, and local communities. The most significant finding is that the field needs to transform its ecosystem low-awareness approach into the integration approach while addressing international networks, scientific research, holistic thinking, sustainability, and education. As a contribution, this article presents a more comprehensive evaluation of the issue of ecosystem regarding natural disaster management (as a common frame) than previous studies.     

The Ecosystem Approach and the Search for An Objective and Content for the Concept of Holistic Ocean Governance

Although the need for holistic ocean governance has been widely accepted and some implementation efforts have been undertaken, there is still a significant lack of understanding or agreement as to its content, or primary objective(s). While both principled and process-based approaches have been proposed as providing objectives or content for the holistic approach, both have flaws. In this article, an approach that combines both principle and process—the ecosystem approach—is assessed and the degree to which it can provide and does already provide such content and objective(s) is explored.     

Meta‐analysis reveals complex marine biological responses to the interactive effects of ocean acidification and warming

Ocean acidification and warming are considered two of the greatest threats to marine biodiversity, yet the combined effect of these stressors on marine organisms remains largely unclear. Using a meta‐analytical approach, we assessed the biological responses of marine organisms to the effects of ocean acidification and warming in isolation and combination. As expected biological responses varied across taxonomic groups, life‐history stages, and trophic levels, but importantly, combining stressors generally exhibited a stronger biological (either positive or negative) effect. Using a subset of orthogonal studies, we show that four of five of the biological responses measured (calcification, photosynthesis, reproduction, and survival, but not growth) interacted synergistically when warming and acidification were combined. The observed synergisms between interacting stressors suggest that care must be made in making inferences from single‐stressor studies. Our findings clearly have implications for the development of adaptive management strategies particularly given that the frequency of stressors interacting in marine systems will be likely to intensify in the future. There is now an urgent need to move toward more robust, holistic, and ecologically realistic climate change experiments that incorporate interactions. Without them accurate predictions about the likely deleterious impacts to marine biodiversity and ecosystem functioning over the next century will not be possible.     

Singing streams: Describing freshwater soundscapes with the help of acoustic indices

1. Understanding soundscapes, that is, the totality of sounds within a location, helps to assess nature in a more holistic way, providing a novel approach to investigating ecosystems. To date, very few studies have investigated freshwater soundscapes in their entirety and none across a broad spatial scale.
2. In this study, we recorded 12 freshwater streams in South East Queensland continuously for three days and calculated three acoustic indices for each minute in each stream. We then used principal component analysis of summary statistics for all three acoustic indices to investigate acoustic properties of each stream and spatial variation in their soundscapes.
3. All streams had a unique soundscape with most exhibiting diurnal variation in acoustic patterns. Across these sites, we identified five distinct groups with similar acoustic characteristics. We found that we could use summary statistics of AIs to describe daytimes across streams as well. Most difference in stream soundscapes was observed during the daytime with significant variation in soundscapes both between hours and among sites.
4. Synthesis and Application. We demonstrate how to characterize stream soundscapes by using simple summary statistics of complex acoustic indices. This technique allows simple and rapid investigation of streams with similar acoustic properties and the capacity to characterize them in a holistic and universal way. While we developed this technique for freshwater streams, it is also applicable to terrestrial and marine soundscapes.

     

Inferring Cell-Scale Signalling Networks via Compressive Sensing

Signalling network inference is a central problem in system biology. Previous studies investigate this problem by independently inferring local signalling networks and then linking them together via crosstalk. Since a cellular signalling system is in fact indivisible, this reductionistic approach may have an impact on the accuracy of the inference results. Preferably, a cell-scale signalling network should be inferred as a whole. However, the holistic approach suffers from three practical issues: scalability, measurement and overfitting. Here we make this approach feasible based on two key observations: 1) variations of concentrations are sparse due to separations of timescales; 2) several species can be measured together using cross-reactivity. We propose a method, CCELL, for cell-scale signalling network inference from time series generated by immunoprecipitation using Bayesian compressive sensing. A set of benchmark networks with varying numbers of time-variant species is used to demonstrate the effectiveness of our method. Instead of exhaustively measuring all individual species, high accuracy is achieved from relatively few measurements.     

Comprehensive proteomic datasets for studying adipocyte–macrophage cell–cell communication

Cellular communication is a fundamental process in biology. The interaction of adipocytes with macrophages is a key event in the development of common diseases such as type 2 diabetes. We applied an established bilayer cell coculture system and comprehensive MS detection to analyse on a proteome‐wide scale the paracrine interaction of murine adipocytes and macrophages. Altogether, we identified 4486 proteins with at least two unique peptides, of which 2392 proteins were informative for 3T3‐L1 adipocytes and 2957 proteins for RAW 264.7 macrophages. Further, we observed over 12000 phosphorylation sites, of which we could assign 3200 informative phosphopeptides with a single phosphosite for adipocytes and 4514 for macrophages. Using protein set enrichment and phosphosite analyses, we deciphered regulatory protein pathways involved in cellular stress and inflammation, which can contribute to metabolic impairment of cells including insulin resistance and other disorders. The generated datasets provide a holistic, molecular pathway‐centric view on the interplay of adipocytes and macrophages in disease processes and a resource for further studies.     

Future directions in the study of induced plant responses to herbivory

This paper reviews current progress and makes recommendations for future studies of induced plant responses to herbivory in three research areas: the role of induction in structuring herbivore communities, costs associated with the expression of induced responses, and theory and data on the macro‐evolution of induced responses. It is argued that although mechanistic approaches will be important for progress, it is also critical to maintain a holistic approach, including a consideration of field environments, multi‐species interactions, and patterns over ecological and evolutionary time.     

A Frailty‐Model‐Based Approach to Estimating the Age‐Dependent Penetrance Function of Candidate Genes Using Population‐Based Case‐Control Study Designs: An Application to Data on the BRCA1 Gene

Summary The population‐based case–control study design is perhaps one of, if not the most, commonly used designs for investigating the genetic and environmental contributions to disease risk in epidemiological studies. Ages at onset and disease status of family members are routinely and systematically collected from the participants in this design. Considering age at onset in relatives as an outcome, this article is focused on using the family history information to obtain the hazard function, i.e., age‐dependent penetrance function, of candidate genes from case–control studies. A frailty‐model‐based approach is proposed to accommodate the shared risk among family members that is not accounted for by observed risk factors. This approach is further extended to accommodate missing genotypes in family members and a two‐phase case–control sampling design. Simulation results show that the proposed method performs well in realistic settings. Finally, a population‐based two‐phase case–control breast cancer study of the BRCA1 gene is used to illustrate the method.     

Multivariate statistical monitoring as applied to clean‐in‐place (CIP) and steam‐in‐place (SIP) operations in biopharmaceutical manufacturing

Multivariate statistical process monitoring (MSPM) is becoming increasingly utilized to further enhance process monitoring in the biopharmaceutical industry. MSPM can play a critical role when there are many measurements and these measurements are highly correlated, as is typical for many biopharmaceutical operations. Specifically, for processes such as cleaning‐in‐place (CIP) and steaming‐in‐place (SIP, also known as sterilization‐in‐place), control systems typically oversee the execution of the cycles, and verification of the outcome is based on offline assays. These offline assays add to delays and corrective actions may require additional setup times. Moreover, this conventional approach does not take interactive effects of process variables into account and cycle optimization opportunities as well as salient trends in the process may be missed. Therefore, more proactive and holistic online continued verification approaches are desirable. This article demonstrates the application of real‐time MSPM to processes such as CIP and SIP with industrial examples. The proposed approach has significant potential for facilitating enhanced continuous verification, improved process understanding, abnormal situation detection, and predictive monitoring, as applied to CIP and SIP operations. © 2014 American Institute of Chemical Engineers Biotechnol. Prog., 30:505–515, 2014     

Genetic analysis of the near-infrared spectral phenome of a global Eucalyptus species

Understanding the genetic-based variability in plant phytochemical compounds provides insight into the evolutionary and ecological processes affecting those traits. In some cases, it is an advantage to quantify the holistic phytochemical profile of a sample rather than focus on individual compounds of known interest. Near-infrared (NIR) reflectance spectroscopy provides a means to rapidly characterise the holistic physicochemical profile of biological materials (known as the spectral phenome). To date, most studies examining differences in the spectral phenome between groups and species have not been conducted in such a way as to enable the quantitative genetic basis of the variation in the spectral phenome to be determined. Here, we investigate the genetic-based variation in the spectral phenome of eucalypts focussing on comparisons at multiple scales of the genetic hierarchy using a tree species of global economic importance, Eucalyptus globulus. Using foliage collected from common-environment field trials we were able to use the spectral phenome to accurately differentiate advanced generation inter-specific hybrids and their parents and examine the pattern of inheritance of the holistic chemical profile. We also found intra-specific variability in the spectral phenome at the race, sub-race and family within race levels, and could identify clear genomic positions influencing the spectral phenome. We have used Eucalyptus as a test system to demonstrate the general approach of using the spectral phenome in genetic-based analyses, an approach that is readily transferrable to other plant systems.     

Palaeoecology and long-term human impact in plant biology

Human impact is a collective concept that requires a holistic approach. Human needs eventually caused the development of cultural landscapes that are at the base of the current landscapes. The papers included in this special issue are evidence that cooperation between different disciplines helps to understand the trend of environmental transformation from past to future. Palaeoecology studies ecosystems of the past and needs archaeology to deepen sociocultural intervention in environmental patterns. In a similar way, ecologists have to include the complexity of societies and economies into landscape ecology by adding principles of human ecology into sustainability science. A brief history of previous actions encouraging the integration of palynology, archaeobotany, archaeology, botany and ecology is reported. The application of integrated studies comes to a new point, the research on the Long-Term Human Impact.     

Interpretation of network-based integration from multi-omics longitudinal data

Multi-omics integration is key to fully understand complex biological processes in an holistic manner. Furthermore, multi-omics combined with new longitudinal experimental design can unreveal dynamic relationships between omics layers and identify key players or interactions in system development or complex phenotypes. However, integration methods have to address various experimental designs and do not guarantee interpretable biological results. The new challenge of multi-omics integration is to solve interpretation and unlock the hidden knowledge within the multi-omics data. In this paper, we go beyond integration and propose a generic approach to face the interpretation problem. From multi-omics longitudinal data, this approach builds and explores hybrid multi-omics networks composed of both inferred and known relationships within and between omics layers. With smart node labelling and propagation analysis, this approach predicts regulation mechanisms and multi-omics functional modules. We applied the method on 3 case studies with various multi-omics designs and identified new multi-layer interactions involved in key biological functions that could not be revealed with single omics analysis. Moreover, we highlighted interplay in the kinetics that could help identify novel biological mechanisms. This method is available as an R package netOmics to readily suit any application.     

DNA barcoding and community assembly—A simple solution to a complex problem

Identifying the current and past processes driving community assembly is critical in the effort to understand the Earth's biodiversity and its response to future environmental change. But while studies on community assembly often emphasize the role of contemporary ecological drivers, it has been particularly challenging to account for the effects of past processes in shaping present‐day communities. In this issue of Molecular Ecology, Hao et al. (2020) provide a holistic analysis of factors driving the assembly of diverse communities of Lepidoptera in two mountain ranges in northeastern China. The authors use an impressively large data set and exceptionally comprehensive analyses to test how processes of range expansion and gene flow, speciation and extinction, dispersal limitation, environmental filtering and competition have led to present‐day diversity patterns. A key novelty of this work is the exhaustive use of DNA barcodes, relatively simple yet powerful molecular markers, to tackle complex biological questions. The authors elegantly show the utility of DNA barcoding data for research beyond simple taxonomic assignment. Their approach is remarkable as it manages to integrate population genetics, phylogenetic history, species diversity and ecology into a well‐rounded picture of community assembly. With this work, Hao et al. demonstrate the great promise of DNA barcoding for exhaustive community analysis of even highly diverse and complex systems, raising the bar for future research.