Application Of Systems Biology Approaches Research Articles

Exploration of the Noncoding Genome for Human-Specific Therapeutic Targets-Recent Insights at Molecular and Cellular Level.

While it is well known that 98-99% of the human genome does not encode proteins, but are nevertheless transcriptionally active and give rise to a broad spectrum of noncoding RNAs [ncRNAs] with complex regulatory and structural functions, specific functions have so far been assigned to only a tiny fraction of all known transcripts. On the other hand, the striking observation of an overwhelmingly growing fraction of ncRNAs, in contrast to an only modest increase in the number of protein-coding genes, during evolution from simple organisms to humans, strongly suggests critical but so far essentially unexplored roles of the noncoding genome for human health and disease pathogenesis. Research into the vast realm of the noncoding genome during the past decades thus lead to a profoundly enhanced appreciation of the multi-level complexity of the human genome. Here, we address a few of the many huge remaining knowledge gaps and consider some newly emerging questions and concepts of research. We attempt to provide an up-to-date assessment of recent insights obtained by molecular and cell biological methods, and by the application of systems biology approaches. Specifically, we discuss current data regarding two topics of high current interest: (1) By which mechanisms could evolutionary recent ncRNAs with critical regulatory functions in a broad spectrum of cell types (neural, immune, cardiovascular) constitute novel therapeutic targets in human diseases? (2) Since noncoding genome evolution is causally linked to brain evolution, and given the profound interactions between brain and immune system, could human-specific brain-expressed ncRNAs play a direct or indirect (immune-mediated) role in human diseases? Synergistic with remarkable recent progress regarding delivery, efficacy, and safety of nucleic acid-based therapies, the ongoing large-scale exploration of the noncoding genome for human-specific therapeutic targets is encouraging to proceed with the development and clinical evaluation of novel therapeutic pathways suggested by these research fields.

Key Challenges in Designing CHO Chassis Platforms

Following the success of and the high demand for recombinant protein-based therapeutics during the last 25 years, the pharmaceutical industry has invested significantly in the development of novel treatments based on biologics. Mammalian cells are the major production systems for these complex biopharmaceuticals, with Chinese hamster ovary (CHO) cell lines as the most important players. Over the years, various engineering strategies and modeling approaches have been used to improve microbial production platforms, such as bacteria and yeasts, as well as to create pre-optimized chassis host strains. However, the complexity of mammalian cells curtailed the optimization of these host cells by metabolic engineering. Most of the improvements of titer and productivity were achieved by media optimization and large-scale screening of producer clones. The advances made in recent years now open the door to again consider the potential application of systems biology approaches and metabolic engineering also to CHO. The availability of a reference genome sequence, genome-scale metabolic models and the growing number of various “omics” datasets can help overcome the complexity of CHO cells and support design strategies to boost their production performance. Modular design approaches applied to engineer industrially relevant cell lines have evolved to reduce the time and effort needed for the generation of new producer cells and to allow the achievement of desired product titers and quality. Nevertheless, important steps to enable the design of a chassis platform similar to those in use in the microbial world are still missing. In this review, we highlight the importance of mammalian cellular platforms for the production of biopharmaceuticals and compare them to microbial platforms, with an emphasis on describing novel approaches and discussing still open questions that need to be resolved to reach the objective of designing enhanced modular chassis CHO cell lines.

Abstract B46: Systems modeling of Ras reveals systems mechanisms that dictate response to treatment

Abstract A relative abundance of biochemical and mechanistic data makes the Ras signaling network an ideal “model system” for the application of systems biology approaches to cancer biology. We here describe our application of systems modeling to the previously unexplained situation where colorectal cancer (CRC) patients with a KRAS G13D mutations are more responsive to anti-EGFR agents than patients with other KRAS mutations. Our computational model of Ras signaling was developed in accordance with the well-established network architecture of RasGTP signal regulation. Measured biochemical and biophysical properties comprise the parameters of the model. The previous biochemical characterization of specific oncogenic mutants allows different oncogenic alleles to be modeled. We use the model to find the behaviors that logically follow from what is known, but which the scope and complexity of the network prevent from otherwise being inferred. We simulated anti-EGFR dose responses for the three most common Ras mutants in CRC: G12D, G12V, and G13D. Our simulations unexpectedly found KRAS G13D was considerably more responsive to anti-EGFR agents. This implies that the known biochemical differences between these mutants are sufficient to explain why KRAS G13D CRC is more sensitive to EGFR inhibition. Our model further predicted that wild-type RasGTP levels within KRAS-mutant cancers should decrease much more for KRAS G13D cancers than KRAS G12V and KRAS G12D cancers. Our analysis predicted that these variations in wild-type RasGTP levels follow from mutant-specific differences in their interaction with Ras GAPs like the tumor suppressor neurofibromin (NF1). This mechanism explains why KRAS G13D CRC, but not KRAS G12D and G12V CRC, retains a dependency upon EGFR. We have now completed experiments that confirm this systems-level mechanism that governs responsiveness to treatment. Citation Format: Edward C. Stites. Systems modeling of Ras reveals systems mechanisms that dictate response to treatment [abstract]. In: Proceedings of the AACR Special Conference on Targeting RAS-Driven Cancers; 2018 Dec 9-12; San Diego, CA. Philadelphia (PA): AACR; Mol Cancer Res 2020;18(5_Suppl):Abstract nr B46.

Systems Biology and Kidney Disease.

The kidney is a complex organ responsible for maintaining multiple aspects of homeostasis in the human body. The combination of distinct, yet interrelated, molecular functions across different cell types make the delineation of factors associated with loss or decline in kidney function challenging. Consequently, there has been a paucity of new diagnostic markers and treatment options becoming available to clinicians and patients in managing kidney diseases. A systems biology approach to understanding the kidney leverages recent advances in computational technology and methods to integrate diverse sets of data. It has the potential to unravel the interplay of multiple genes, proteins, and molecular mechanisms that drive key functions in kidney health and disease. The emergence of large, detailed, multilevel biologic and clinical data from national databases, cohort studies, and trials now provide the critical pieces needed for meaningful application of systems biology approaches in nephrology. The purpose of this review is to provide an overview of the current state in the evolution of the field. Recent successes of systems biology to identify targeted therapies linked to mechanistic biomarkers in the kidney are described to emphasize the relevance to clinical care and the outlook for improving outcomes for patients with kidney diseases.

Trajectories of Aging: How Systems Biology in Yeast Can Illuminate Mechanisms of Personalized Aging.

All organisms age, but the extent to which all organisms age the same way remains a fundamental unanswered question in biology. Across species, it is now clear that at least some aspects of aging are highly conserved and are perhaps universal, but other mechanisms of aging are private to individual species or sets of closely related species. Within the same species, however, it has generally been assumed that the molecular mechanisms of aging are largely invariant from one individual to the next. With the development of new tools for studying aging at the individual cell level in budding yeast, recent data has called this assumption into question. There is emerging evidence that individual yeast mother cells may undergo fundamentally different trajectories of aging. Individual trajectories of aging are difficult to study by traditional population level assays, but through the application of systems biology approaches combined with novel microfluidic technologies, it is now possible to observe and study these phenomena in real time. Understanding the spectrum of mechanisms that determine how different individuals age is a necessary step toward the goal of personalized geroscience, where healthy longevity is optimized for each individual.

Increased growth rate and productivity following stable depletion of miR-7 in a mAb producing CHO cell line causes an increase in proteins associated with the Akt pathway and ribosome biogenesis

Cell line engineering using microRNAs represents a desirable route for improving the efficiency of recombinant protein production by CHO cells. In this study we generated stable CHO DP12 cells expressing a miR-7 sponge transcript which sequesters miR-7 from its endogenous targets. Depletion of miR-7 results in a 65% increase in cell growth and >3-fold increase in yield of secreted IgG protein. Quantitative labelfree LC-MS/MS proteomic profiling was carried out to identify the targets of miR-7 and understand the functional drivers of the improved CHO cell phenotypes. Subcellular enrichment and total proteome analysis identified more than 3000 proteins per fraction resulting in over 5000 unique proteins identified per timepoint analysed. Early stage culture analysis identified 117 proteins overexpressed in miR-7 depleted cells. A subset of these proteins are involved in the Akt pathway which could be the underlying route for cell density improvement and may be exploited more specifically in the future. Late stage culture identified 160 proteins overexpressed in miR-7 depleted cells with some of these involved in ribosome biogenesis which may be causing the increased productivity through improved translational efficiency. This is the first in-depth proteomic profiling of the IgG producing CHO DP12 cell line stably depleted of miR-7. SignificanceChinese hamster ovary (CHO) cells are the mammalian cell expression system of choice for production of recombinant therapeutic proteins. There is much research ongoing to characterise CHO cell factories through the application of systems biology approaches that will enable a fundamental understanding of CHO cell physiology, and as a result, a better knowledge and understanding of recombinant protein production. This study profiles the proteomic effects of microRNA-7 depletion on the IgG producing CHO DP12 cell line. This is one of the very few studies that attempts to identify the functioning proteins driving improved CHO cell phenotypes resulting from microRNA manipulation. Using subcellular enrichment and total proteome analysis we identified over 5000 unique proteins in miR-7 depleted CHO cells. This work has identified a cohort of proteins involved in the Akt pathway and ribosome biogenesis. These proteins may drive improved CHO cell phenotypes and are of great interest for future work.

Hardwood Tree Genomics: Unlocking Woody Plant Biology.

Woody perennial angiosperms (i.e., hardwood trees) are polyphyletic in origin and occur in most angiosperm orders. Despite their independent origins, hardwoods have shared physiological, anatomical, and life history traits distinct from their herbaceous relatives. New high-throughput DNA sequencing platforms have provided access to numerous woody plant genomes beyond the early reference genomes of Populus and Eucalyptus, references that now include willow and oak, with pecan and chestnut soon to follow. Genomic studies within these diverse and undomesticated species have successfully linked genes to ecological, physiological, and developmental traits directly. Moreover, comparative genomic approaches are providing insights into speciation events while large-scale DNA resequencing of native collections is identifying population-level genetic diversity responsible for variation in key woody plant biology across and within species. Current research is focused on developing genomic prediction models for breeding, defining speciation and local adaptation, detecting and characterizing somatic mutations, revealing the mechanisms of gender determination and flowering, and application of systems biology approaches to model complex regulatory networks underlying quantitative traits. Emerging technologies such as single-molecule, long-read sequencing is being employed as additional woody plant species, and genotypes within species, are sequenced, thus enabling a comparative (“evo-devo”) approach to understanding the unique biology of large woody plants. Resource availability, current genomic and genetic applications, new discoveries and predicted future developments are illustrated and discussed for poplar, eucalyptus, willow, oak, chestnut, and pecan.

Diversity and Function of Microbial Community in Chinese Strong-Flavor Baijiu Ecosystem: A Review.

Strong flavor baijiu (SFB), also called Luzhou-flavor liquor, is the most popular Chinese baijiu. It is manufactured via solid fermentation, with daqu as the starter. Microbial diversity of the SFB ecosystem and the synergistic effects of the enzymes and compounds produced by them are responsible for the special flavor and mouthfeel of SFB. The present review covers research studies focused on microbial community analysis of the SFB ecosystem, including the culturable microorganisms, their metabolic functions, microbial community diversity and their interactions. The review specifically emphasizes on the most recently conducted culture-independent analysis of SFB microbial community diversity. Furthermore, the possible application of systems biology approaches for elucidating the molecular mechanisms of SFB production were also reviewed and prospected.

Systems Biology-Based Platforms to Accelerate Research of Emerging Infectious Diseases.

Emerging infectious diseases (EIDs) pose a major threat to public health and security. Given the dynamic nature and significant impact of EIDs, the most effective way to prevent and protect against them is to develop vaccines in advance. Systems biology approaches provide an integrative way to understand the complex immune response to pathogens. They can lead to a greater understanding of EID pathogenesis and facilitate the evaluation of newly developed vaccine-induced immunity in a timely manner. In recent years, advances in high throughput technologies have enabled researchers to successfully apply systems biology methods to analyze immune responses to a variety of pathogens and vaccines. Despite recent advances, computational and biological challenges impede wider application of systems biology approaches. This review highlights recent advances in the fields of systems immunology and vaccinology, and presents ways that systems biology-based platforms can be applied to accelerate a deeper understanding of the molecular mechanisms of immunity against EIDs.

Editorial: Systems Biology of Transcription Regulation

Editorial: Systems Biology of Transcription Regulation

Antiviral innate immunity through the lens of systems biology

Cellular innate immunity poses the first hurdle against invading viruses in their attempt to establish infection. This antiviral response is manifested with the detection of viral components by the host cell, followed by transduction of antiviral signals, transcription and translation of antiviral effectors and leads to the establishment of an antiviral state. These events occur in a rather branched and interconnected sequence than a linear path. Traditionally, these processes were studied in the context of a single virus and a host component. However, with the advent of rapid and affordable OMICS technologies it has become feasible to address such questions on a global scale. In the discipline of Systems Biology’, extensive omics datasets are assimilated using computational tools and mathematical models to acquire deeper understanding of complex biological processes. In this review we have catalogued and discussed the application of Systems Biology approaches in dissecting the antiviral innate immune responses.

Systems Medicine: The Application of Systems Biology Approaches for Modern Medical Research and Drug Development.

The exponential development of highly advanced scientific and medical research technologies throughout the past 30 years has arrived to the point where the high number of characterized molecular agents related to pathogenesis cannot be readily integrated or processed by conventional analytical approaches. Indeed, the realization that several moieties are signatures of disease has partly led to the increment of complex diseases being characterized. Scientists and clinicians can now investigate and analyse any individual dysregulations occurring within the genomic, transcriptomic, miRnomic, proteomic, and metabolomic levels thanks to currently available advanced technologies. However, there are drawbacks within this scientific brave new age in that only isolated molecular levels are individually investigated for their influence in affecting any particular health condition. Since their conception in 1992, systems biology/medicine focuses mainly on the perturbations of overall pathway kinetics for the consequent onset and/or deterioration of the investigated condition/s. Systems medicine approaches can therefore be employed for shedding light in multiple research scenarios, ultimately leading to the practical result of uncovering novel dynamic interaction networks that are critical for influencing the course of medical conditions. Consequently, systems medicine also serves to identify clinically important molecular targets for diagnostic and therapeutic measures against such a condition.

Evolving toward a human-cell based and multiscale approach to drug discovery for CNS disorders.

A disruptive approach to therapeutic discovery and development is required in order to significantly improve the success rate of drug discovery for central nervous system (CNS) disorders. In this review, we first assess the key factors contributing to the frequent clinical failures for novel drugs. Second, we discuss cancer translational research paradigms that addressed key issues in drug discovery and development and have resulted in delivering drugs with significantly improved outcomes for patients. Finally, we discuss two emerging technologies that could improve the success rate of CNS therapies: human induced pluripotent stem cell (hiPSC)-based studies and multiscale biology models. Coincident with advances in cellular technologies that enable the generation of hiPSCs directly from patient blood or skin cells, together with methods to differentiate these hiPSC lines into specific neural cell types relevant to neurological disease, it is also now possible to combine data from large-scale forward genetics and post-mortem global epigenetic and expression studies in order to generate novel predictive models. The application of systems biology approaches to account for the multiscale nature of different data types, from genetic to molecular and cellular to clinical, can lead to new insights into human diseases that are emergent properties of biological networks, not the result of changes to single genes. Such studies have demonstrated the heterogeneity in etiological pathways and the need for studies on model systems that are patient-derived and thereby recapitulate neurological disease pathways with higher fidelity. In the context of two common and presumably representative neurological diseases, the neurodegenerative disease Alzheimer’s Disease, and the psychiatric disorder schizophrenia, we propose the need for, and exemplify the impact of, a multiscale biology approach that can integrate panomic, clinical, imaging, and literature data in order to construct predictive disease network models that can (i) elucidate subtypes of syndromic diseases, (ii) provide insights into disease networks and targets and (iii) facilitate a novel drug screening strategy using patient-derived hiPSCs to discover novel therapeutics for CNS disorders.

Immunity to viruses

The analysis of the innate and adaptive immune response to viruses has provided fundamental insight into the functioning of the immune system. Early studies on the host response to virus infection were instrumental in establishing the concept of immunological tolerance (1). Similarly, the realization that T lymphocytes are ‘restricted’ in their recognition of antigens by gene products encoded within the major histocompatibility complex (MHC) locus came from the analysis of T-lymphocyte recognition of virus-infected cells (2). Likewise, important initial insights into antigen processing and presentation came from the analysis of viruses and virus-infected cells (3, 4). Until recently, it was convenient to view immunity to infectious agents like viruses as a separate branch of immunology distinct from immunity to tumors, self-molecules (antigens), or allergens. As demonstrated in many of the articles in this volume of Immunological Reviews, the mechanisms underlying the induction and regulation of the innate and adaptive immune response to viruses represent the same processes controlling immunity to tumor antigens, allergens, and self-constituents. Thus, the results summarized in these review articles and the implications of these findings are applicable not only to those of us who study immunity to viruses but also to the immunology community at large. In selecting the topics for review in this volume of Immunological Reviews, we were first and foremost limited by space. Consequently, many important contributors to the field of viral immunology (indeed several topics) are not represented in this volume. Our selection of topics and authors was biased towards emerging areas, such as the application of systems biology approaches to viral pathogenesis and immunity, the contribution of inflammatory and stress responses to the induction of Innate and adaptive immune responses, and the impact of the microbiome on immunity to virus infection. We also considered it relevant to include reviews focused on well defined areas where recent findings have resulted in potential paradigm shifts in our understanding of topics such as B-lymphocyte or T-lymphocyte responses to virus infection. This volume of Immunological Reviews is also somewhat weighted towards analyses of the immune response to respiratory viruses. With the recent episodic infections with the severe acute respiratory syndrome (SARS)-like coronavirus and the outbreak of human infections with the avian influenza A H7N9 virus, respiratory viruses such as these organisms are recognized as major human pathogens with the potential for pandemic spread. Therefore, this class of viruses is a focus of immunological research. The reviews in this volume can be grouped according to the following scheme: (i) molecules and cells regulating the induction of the innate and adaptive response, (ii) expression of immune effector activity, (iii) regulation of the antiviral immune response, and (iv) systems analysis of the host response to infection and vaccination (Fig. 1). Fig. 1 Immunity to viruses

The road from systems biology to systems medicine

As research institutions prepare roadmaps for "systems medicine," we ask how this differs from applications of systems biology approaches in medicine and what we (should) have learned from about one decade of funding in systems biology. After surveying the area, we conclude that systems medicine is the logical next step and necessary extension of systems biology, and we focus on clinically relevant applications. We specifically discuss three related notions. First, more interdisciplinary collaborations are needed to face the challenges of integrating basic research and clinical practice: integration, analysis, and interpretation of clinical and nonclinical data for diagnosis, prognosis, and therapy require advanced statistical, computational, and mathematical tools. Second, strategies are required to (i) develop and maintain computational platforms for the integration of clinical and nonclinical data, (ii) further develop technologies for quantitative and time-resolved tracking of changes in gene expression, cell signaling, and metabolism in relation to environmental and lifestyle influences, and (iii) develop methodologies for mathematical and statistical analyses of integrated data sets and multilevel models. Third, interdisciplinary collaborations represent a major challenge and are difficult to implement. For an efficient and successful initiation of interdisciplinary systems medicine programs, we argue that epistemological, ontological, and sociological aspects require attention.

Participatory medicine: a driving force for revolutionizing healthcare

Healthcare is undergoing a profound revolution as a consequence of three contemporary thrusts: systems medicine [1-4], big data and patient involvement in their own health through social networks. This convergence is leading to a medicine that is predictive, preventive, personalized and participatory (P4) [4-7]. The first three Ps, predictive, preventive and personalized, were delineated in the early 2000s [1,2], whereas the fourth P, participatory, was added later. To achieve a participatory healthcare system, major technical and societal challenges will need to be overcome, and this will require close integration with systems medicine and big data. Before commenting further on participatory medicine, let us first delineate the essence of systems medicine and big data and their implications for P4 medicine. Systems medicine, the application of systems biology approaches to disease [3,4,6,8,9], is already changing how healthcare is practiced (Table 1). We predict that in 5 to 10 years each patient will be surrounded by a virtual cloud of billions of data points - molecular, clinical chemistries, cellular, organ, phenotypic, imaging, social networks, and so on. We also predict that we will have the analytical tools to reduce this big data cloud to simple models that will guide improvements in health and minimize disease. This requires addressing two grand challenges: the signal-to-noise issues intrinsic to big data and integration of multi-scale data into predictive models. Table 1 How systems medicine is transforming healthcare In addition, for each individual patient we foresee that we will be able to integrate an individual’s genetic, molecular, cellular, organ and social networks into an overall 'network of networks’ [10]. Disease leads to the perturbation of the network of networks and this alters the information the network manages. The availability of a personal data cloud will allow one to characterize an individual’s network of networks in its normal or disease-perturbed states. This altered, disease-perturbed information will provide deep insights into disease mechanisms, new approaches to diagnostics and therapeutics, and a platform for participatory medicine.

Hormone Signaling Networks Open Multiple Routes for Immunity and Disease in Plants

Plant hormones are small signaling molecules that regulate almost every aspect of plant life cycle. Plant pathogens alter hormonal balance of the host to cause disease. In response, host redefines hormone signaling networks to cope with the invading pathogen. Biotrophic pathogens are generally sensitive to salicylic acid mediated defense responses, whereas necrotrophic pathogens are deterred through jasmonate/ethylene pathways. Interaction between these pathways is regarded as central backbone of plant immunity. Classic hormones such as auxin, gibberellin, and cytokinin either promote salicylic acid or jasmonates mediated networks of immunity in plants. Here, we advocate a network biology perspective and emphasize the application of systems biology approaches for a comprehensive understanding of plantpathogen interactions.

Obituary: Ajit Dhaunchak, Ph.D

On the 18th of August 2012, Ajit Singh Dhaunchak passed away at the age of 33 in Quebec, Canada. His tragic and premature death was a terrible loss to his family, friends and colleagues, all of whom miss his dynamic personality and ever-smiling presence. At his funereal, Phil Barker, interim director of the Montreal Neurological Institute (MNI) at the time, emphasized how Ajit embodied that rare strain of scientist who combines gifted intellect, hard working, and seemingly endless stamina, with a most personable and charismatic personality— a remarkable set of qualities with which Ajit engaged and inspired all around him. Here, we wish to remember aspects of Ajit’s professional life that reinforce Dr. Barker’s observation and pay homage to a dear colleague and friend who, in all too short a life, already made important contributions to the field of neuroscience. Ajit was born on August 1, 1979 in the city of Chandigarh, India, where he grew up and later entered the Panjab University to study Biophysics. Even as an undergraduate student he took a keen interest in understanding complex biological processes. When others were struggling to make sense of the course material, he could be seen reading books on protein chemistry and other topics well beyond the scope of the assigned course work. Apart from being an inspired student Ajit was also a gifted sportsman. Whether as an undergraduate student in India, a Ph.D student in Germany, or a postdoc in Canada—he always found time and friends to play his two favorite games— Cricket and Chess. After graduating from Panjab University, Ajit left India, and moved to Germany where he enrolled in an integrated M.Sc-Ph.D program at the Max Planck Institute for Experimental Medicine. As a Ph.D student in the lab of Prof. Klaus-Armin Nave, he was introduced to the field of myelin biology and white matter diseases. His Ph.D research focused on the major myelin protein, proteolipid protein (PLP), and its mutations in association to Pelizaeus-Merzbacher disease (PMD). A paper published in Journal of Cell Biology, which summarizes part of the results obtained during his Ph.D, demonstrates that neuron-glia interactions regulate cell-surface expression of PLP in oligodendrocytes (Trajkovic et al., 2006). A second paper, published in PNAS, demonstrates that PMD-related mutations localized to the extracellular loop of PLP lead to protein cross-linking and PLP retention in the endoplasmic reticulum (Dhaunchak and Nave, 2007). Ajit was one of the very few students who managed to defend their Ph.D thesis in less than 3 years. In 2007, soon after completing his Ph.D, Ajit joined the MNI and McGill University in Quebec, Canada, as a post-doctoral fellow in the laboratory of the late Dr. David R. Colman. There, Ajit continued to study PLP while also expanding his research interests and establishing several productive collaborations to investigate complementary aspects of white matter biology. He became particularly interested in the application of systems-biology approaches to the study of myelin and myelin diseases. In this context, Ajit made important contributions to our knowledge of the myelin proteome, lipidome, and transcriptome, both in health and disease. In work published in Glia, Ajit and colleagues provide a catalogue of novel proteins identified in axoglial specializations isolated from the human Central Nervous System (Dhaunchak et al., 2010). In another proteomic study lead by Ajit and featured in Annals of Neurology, a collaborative study by the Canadian Pediatric Demyelinating Disease Network provided evidence indicating that the myelin axoglial apparatus is disrupted at early stages of childhoodonset Multiple Sclerosis (Dhaunchak et al., 2012). In all, Ajit published eight papers during his post-doc in leading neuroscience journals and initiated or became involved in several other projects that continue even after his death. During his last few months at the MNI, Ajit was busy writing project proposals and preparing for job interviews. Anyone listening to him practice a job talk had the distinct impression that in fact Ajit had already been running an active lab for several years, reflecting the large amount of quality data he had generated as well as his deep overall grasp of the field. There was no doubt Ajit was to become a most successful independent researcher, and everyone from fellow trainees to principle investigators at the MNI were certain that it’s just a matter of time before he would get the position he wanted.

Towards systems biological understanding of leaf senescence

The application of systems biology approaches has greatly facilitated the process of deciphering the molecular mechanisms underlying leaf senescence. Analyses of the leaf senescence transcriptome have identified some of the major biochemical events during senescence including protein degradation and nutrient remobilization. Proteomic studies have confirmed these findings and have suggested up-regulated energy metabolism during leaf senescence which might be important for cell viability maintenance. As a critical part of systems biology, studies involving transcription regulation networking and senescence-inducing signaling have deepened our understanding on the molecular regulation of leaf senescence. The important next steps towards a systems biological understanding of leaf senescence will be discussed.

Systems Biology in Aging: Linking the Old and the Young

Aging can be defined as a process of progressive decline in the physiological capacity of an organism, manifested by accumulated alteration and destabilization at the whole system level. Systems biology approaches offer a promising new perspective to examine the old problem of aging. We begin this review by introducing the concepts of systems biology, and then illustrate the application of systems biology approaches to aging research, from gene expression profiling to network analysis. We then introduce the network that can be constructed using known lifespan and aging regulators, and conclude with a look forward to the future of systems biology in aging research. In summary, systems biology is not only a young field that may help us understand aging at a higher level, but also an important platform that can link different levels of knowledge on aging, moving us closer to a more comprehensive control of systematic decline during aging.