Lilia Alberghina

Università degli Studi di Milano-Bicocca | UNIMIB

Neuronal differentiation is regulated by nerve growth factor (NGF) and other neurotrophins. We explored the impact of NGF on mitochondrial dynamics and metabolism through time‐lapse imaging, metabolomics profiling, and computer modeling studies. We show that NGF may direct differentiation by stimulating fission, thereby causing selective mitochondr...

For unicellular organisms, the reproduction rate and growth are crucial determinants of fitness and, therefore, essential functional manifestations of the organism genotype. Using the budding yeast Saccharomyces cerevisiae as a model organism, we integrated metabolism, which provides energy and building blocks for growth, with cell mass growth and...

The Warburg effect is the long-standing riddle of cancer biology. How does aerobic glycolysis, inefficient in producing ATP, confer a growth advantage to cancer cells? A new evaluation of a large set of literature findings covering the Warburg effect and its yeast counterpart, the Crabtree effect, led to an innovative working hypothesis presented h...

Cyclin-dependent kinase 12 (CDK12) overexpression is implicated in breast cancer, but whether it has a primary or only a cooperative tumorigenic role is unclear. Here, we show that transgenic CDK12 overexpression in the mouse mammary gland per se is sufficient to drive the emergence of multiple and multifocal tumors, while, in cooperation with know...

Metabolism is directly and indirectly fine-tuned by a complex web of interacting regulatory mechanisms that fall into two major classes. On the one hand, the expression level of the catalyzing enzyme sets the maximal theoretical flux level (i.e., the net rate of the reaction) for each enzyme-controlled reaction. On the other hand, metabolic regulat...

Rewiring glucose metabolism toward aerobic glycolysis provides cancer cells with a rapid generation of pyruvate, ATP, and NADH, while pyruvate oxidation to lactate guarantees refueling of oxidized NAD+ to sustain glycolysis. CtPB2, an NADH-dependent transcriptional co-regulator, has been proposed to work as an NADH sensor, linking metabolism to epi...

Background Artificial intelligence (AI) has the potential to transform our healthcare systems significantly. New AI technologies based on machine learning approaches should play a key role in clinical decision-making in the future. However, their implementation in health care settings remains limited, mostly due to a lack of robust validation proce...

Metabolism is directly and indirectly fine-tuned by a complex web of interacting regulatory mechanisms that fall into two major classes. First, metabolic regulation controls metabolic fluxes (i.e., the rate of individual metabolic reactions) through the interactions of metabolites (substrates, cofactors, allosteric modulators) with the responsible...

How the network around ROS protects against oxidative stress and Parkinson’s disease (PD), and how processes at the minutes timescale cause disease and aging after decades, remains enigmatic. Challenging whether the ROS network is as complex as it seems, we built a fairly comprehensive version thereof which we disentangled into a hierarchy of only...

Background: Rewiring of metabolism induced by oncogenic K-Ras in cancer cells involves both glucose and glutamine utilization sustaining enhanced, unrestricted growth. The development of effective anti-cancer treatments targeting metabolism may be facilitated by the identification and rational combinatorial targeting of metabolic pathways. Method...

In early 2020 the new respiratory syndrome COVID‐19 (caused by the zoonotic SARS‐CoV‐2 virus) spread like a pandemic, starting from Wuhan, China, causing severe economic depression. Despite some advances in drug treatments of medical complications in the later stages of the disease, the pandemic's death toll is tragic, as no vaccine or specific ant...

Metabolomics is a rapidly expanding technology that finds increasing application in a variety of fields, form metabolic disorders to cancer, from nutrition and wellness to design and optimization of cell factories. The integration of metabolic snapshots with metabolic fluxes, physiological readouts, metabolic models, and knowledge-informed Artifici...

Nicotinamide, nicotinic acid and nicotinamide riboside are vitamin B3 precursors of NAD+ in the human diet. NAD+ has a fundamental importance for cellular biology, that derives from its essential role as a cofactor of various metabolic redox reactions, as well as an obligate co-substrate for NAD+-consuming enzymes which are involved in many fundame...

The synaptic cleft has been vastly investigated in the last decades, leading to a novel and fascinating model of the functional and structural modifications linked to synaptic transmission and brain processing. The classic neurocentric model encompassing the neuronal pre- and post-synaptic terminals partly explains the fine-tuned plastic modificati...

Laboratory models derived from clinical samples represent a solid platform in preclinical research for drug testing and investigation of disease mechanisms. The integration of these laboratory models with their digital counterparts (i.e., predictive mathematical models) allows to set up digital twins essential to fully exploit their potential to fa...

Motivation: The elucidation of dysfunctional cellular processes that can induce the onset of a disease is a challenging issue from both experimental and computational perspectives. Here we introduce a novel computational method based on the coupling between fuzzy logic modeling and a global optimization algorithm, whose aims are to (1) predict the...

Neuroinflammation, a hallmark of chronic neurodegenerative disorders, is characterized by sustained glial activation and the generation of an inflammatory loop, through the release of cytokines and other neurotoxic mediators that cause oxidative stress and limit functional repair of brain parenchyma. Dietary antioxidants may protect against neurode...

The eminently complex regulatory network protecting the cell against oxidative stress, surfaces in several disease maps, including that of Parkinson’s disease (PD). How this molecular networking achieves its various functionalities and how processes operating at the seconds-minutes time scale cause a disease at a time scale of multiple decennia is...

Metabolic reprogramming is a general feature of cancer cells. Regrettably, the comprehensive quantification of metabolites in biological specimens does not promptly translate into knowledge on the utilization of metabolic pathways. By estimating fluxes across metabolic pathways, computational models hold the promise to bridge this gap between data...

Sensitivity of scFBA results to ϵ for LCPT45 dataset. A) Left: histogram of biomass produced by each single cell when ϵ = 0. Right: Total biomass produced by the population of cells as a function of ϵ. The inset reports the same curve zoomed in on low ϵ values. B) Clustergram (distance metric: euclidean) of the effect of single gene deletions perfo...

Clustering of transcripts vs. fluxes. A) H358 dataset. Clustergram (distance metric: euclidean) of the transcripts of the metabolic genes included in metabolic network (left) and of the metabolic fluxes predicted by scFBA (middle). Right panel: elbow analysis comparing cluster errors for k ∈ {1, ⋯, 20} (k-means clustering) in both transcripts (blue...

scFBA computation time. The linear relationship between the time for an FBA (and thus a scFBA) optimization and the size of the network is well established. We estimated the computation time required to perform a complete model reconstruction, from a template metabolic network to a population model with RASs integrated, for different number of cell...

Comparison of the fluxes predicted by scFBA, GIMME and iMAT with respect to LCPT45 dataset. (XLSX)

scFBA vs. popFBA. A) Dataset H358. Variability of the fraction of the biomass synthesis flux (logarithmic scale) for each cell over the population growth rate (left panel) before (purple) and after data integration (green). Effect of gene deletion (bars in right panel) on the population growth rate before (popFBA), after data integration (scFBA), a...

Description of sensitivity of scFBA results to ϵ. (PDF)

Evaluation of clustering goodness. (PDF)

Comparison of the fluxes of the two main clusters in Fig 3A-middle. (XLSX)

The recognition that neurogenesis does not stop with adolescence has spun off research towards the reduction of brain disorders by enhancing brain regeneration. Adult neurogenesis is one of the tougher problems of developmental biology as it requires the generation of complex intracellular and pericellular anatomies, amidst the danger of neuroinfla...

Coagulation and the immune system interact in several physiological and pathological conditions, including tissue repair, host defense, and homeostatic maintenance. This network plays a key role in diseases of the central nervous system (CNS) by involving several cells (CNS resident cells, platelets, endothelium, and leukocytes) and molecular pathw...

One of the most challenging fields in Life Science research is to deeply understand how complex cellular functions arise from the interactions of molecules in living cells. Mathematical and computational methods in Systems Biology are fundamental to study the complex molecular interactions within biological systems and to accelerate discoveries. Wi...

One of the most challenging fields in Life Science research is to deeply understand how complex cellular functions arise from the interactions of molecules in living cells. Mathematical and computational methods in Systems Biology are fundamental to study the complex molecular interactions within biological systems and to accelerate discoveries. Wi...

Mitochondria play essential metabolic functions in eukaryotes. Although their major role is the generation of energy in the form of ATP, they are also involved in maintenance of cellular redox state, conversion and biosynthesis of metabolites and signal transduction. Most mitochondrial functions are conserved in eukaryotic systems and mitochondrial...

Coordinated sets of extremely numerous digital data, on a given social or economic event, are treated by Artificial Intelligence tools to obtain reasonably accurate, valuable predictions. The same approach, applied to biomedical issues, as how to choose the right drug to completely cure a given cancer patient, does not reach satisfactory results. I...

Computational models are expected to increase understanding of how complex biological functions arise from the interactions of large numbers of gene products and biologically active low molecular weight molecules. Recent studies underline the need to develop quantitative models of the whole cell in order to tackle this challenge and to accelerate b...

Neuronal differentiation involves extensive modification of biochemical and morphological properties to meet novel functional requirements. Reorganization of the mitochondrial network to match the higher energy demand plays a pivotal role in this process. Mechanisms of neuronal differentiation in response to nerve growth factor (NGF) have been larg...

Motivation Metabolic reprogramming is a general feature of cancer cells. Regrettably, the comprehensive quantification of metabolites in biological specimens does not promptly translate into knowledge on the utilization of metabolic pathways. Computational models hold the promise to bridge this gap, by estimating fluxes across metabolic pathways. Y...

Cancer cells share several metabolic traits, including aerobic production of lactate from glucose (Warburg effect), extensive glutamine utilization and impaired mitochondrial electron flow. It is still unclear how these metabolic rearrangements, which may involve different molecular events in different cells, contribute to a selective advantage for...

Analytical computations supporting simulation results in Fig 6. For different possible flux routes (table rows), the P/O ratio (column 8) of as well as the moles of acetyl-CoA deriving form one mole of substrate (column 10) following the considered route is computed. In some cases, the row indicates the difference between the computations of two po...

ENGRO1 SBML model. Excel file of the model compliant with: RAVEN Toolbox and FAME. (XML)

ENGRO1 SVG map. Scalable Vector Graphics image of the model, compliant with the software FAME. (SVG)

ENGRO1 biomass optimization for different boundary conditions (supplement to Fig 4). All data derive from Flux Variability Analysis in experiments that maximize biomass production. All reported fluxes do not show variability in optimal solutions. All glucose available is always fully consumed in these simulations. A) Growth rate (z-axis) and oxygen...

Interplay among the sub-networks showing alternative flux patterns in Fig 5. The first sub-network (shaded polygon, with the exception of pyruvate carboxylase) includes PEP carboxykinase; pyruvate kinase, NADP and NAD dependent malic enzyme and malate dehydrogenase. Because the TCA cycle is working in a non-cyclic mode, this set of reactions allows...

Experimental raw data. Raw data (enzyme assays, growth curves, metabolomics) used to build graphs in Fig 3. (XLS)

Supplemental text. Biochemical interpretation of experimental results. (PDF)

ENGRO1 excel model. Excel file of the model compliant with the RAVEN Toolbox. (XLS)

Similarity of results obtained when oxygen consumption is modulated by altering either oxygen availability (as in Fig 4) or Complex I capacity (flux upper bound). Note that because of the reaction stoichiometry, Complex I flux is proportionally higher than the corresponding oxygen consumption rate. A-B) Growth rate scaled on glucose availability as...

On why glutamine is the preferred anaplerotic precursor (supplement to Fig 6). A) Maximum and minimum value for lactate secretion across optimal growth solutions according to FVA, as a function of the parameter pROS that emulates the level of production of reactive oxygen species in the respiratory chain (see S1 Supplemental Methods). Glucose avail...

Determination of sample size. A) Standard deviation of the model fluxes (represented with different colors) as a function of the sample size. B) Zoom in on fluxes of panel A with low standard deviations. The fluxes with high standard deviations correspond to those with high variability when running FVA. C) Relative standard error of the mean of eac...

ENGRO1 flux distribution that maximizes growth at critical O2GR (O2: 38 mM h-1; G: 10 mM h-1; Q: 40 mM h-1). The optimal flux value obtained with FBA, the minimum and maximum value as well as the range size, obtained with FVA, are reported for each reaction. (XLSX)

ENGRO1 flux distribution that maximizes ATP production at critical O2GR (O2: 38 mM h-1; G: 10 mM h-1; Q: 40 mM h-1). The optimal flux value obtained with FBA, the minimum and maximum value as well as the range size, obtained with FVA, are reported for each reaction. (XLSX)

Supplemental methods. Details on ENGRO1 model reconstruction. (PDF)

Timing and synchronization mechanisms are ubiquitous in living systems, and in many cases involve switch-like regulators that control complex molecular pathways and cellular functions. The switching of such regulators is often irreversible and controlled by the co-activation of a set of concurrent independent enabling events. Despite the random nat...

Background Recent advances in large datasets analysis offer new insights to modern biology allowing system-level investigation of pathologies. Here we describe a novel computational method that exploits the ever-growing amount of “omics” data to shed light on Alzheimer’s and Parkinson’s diseases. Neurological disorders exhibit a huge number of mole...

Oncogenic K-ras is capable to control tumor growth and progression by rewiring cancer metabolism. In vitro NIH-Ras cells convert glucose to lactate and use glutamine to sustain anabolic processes, but their in vivo environmental adaptation and multiple metabolic pathways activation ability is poorly understood. Here, we show that NIH-Ras cancer cel...

Calcium homeostasis is crucial to eukaryotic cell survival. By acting as an enzyme cofactor and a second messenger in several signal transduction pathways, the calcium ion controls many essential biological processes. Inside the endoplasmic reticulum (ER) calcium concentration is carefully regulated to safeguard the correct folding and processing o...

Systems Biology is an approach to biology and medicine that has the potential to lead to a better understanding of how biological properties emerge from the interaction of genes, proteins, molecules, cells and organisms. The approach aims at elucidating how these interactions govern biological function by employing experimental data, mathematical m...

In budding yeast, overcoming of a critical size to enter S phase and the mitosis/mating switch - two central cell fate events - take place in the G 1 phase of the cell cycle. Here we present a mathematical model of the basic molecular mechanism controlling the G 1 /S transition, whose major regulatory feature is multisite phosphorylation of nuclear...

Supplementary Figures 1-19, Supplementary Tables 1-10, Supplementary Notes 1-24 and Supplementary References

Role of functional and decoy phosphosites in the control of timing and coherence of multi-target regulatory events in cell cycle progression. Upper and lower left panels of the movie show a schematic cell nucleus containing SBF-Whi5-controlled G1/S regulon genes. Open circles represent non-transcribed genes, while green circle transcribed genes. Ri...

HSPA8/hsc70 (70-kDa heat shock cognate) chaperone protein exerts multiple protective roles. Beside its ability to confer to the cells a generic resistance against several metabolic stresses, it is also involved in at least two critical processes whose activity is essential in preventing Parkinson’s disease (PD) pathology. Actually, hsc70 protein ac...

Modulation of extracellular matrix (ECM) remodeling after peripheral nerve injury (PNI) could represent a valid therapeutic strategy to prevent maladaptive synaptic plasticity in central nervous system (CNS). Inhibition of matrix metalloproteinases (MMPs) and maintaining a neurotrophic support could represent two approaches to prevent or reduce the...

Cancer cells often rely on glycolysis to obtain energy and support anabolic growth. Several studies showed that glycolytic cells are susceptible to cell death when subjected to low glucose availability or to lack of glucose. However, some cancer cells, including glycolytic ones, can efficiently acquire higher tolerance to glucose depletion, leading...

Cancer cells often rely on glycolysis to obtain energy and support anabolic growth. Several studies showed that glycolytic cells are susceptible to cell death when subjected to low glucose availability or to lack of glucose. However, some cancer cells, including glycolytic ones, can efficiently acquire higher tolerance to glucose depletion, leading...

The genes regulated by FSK in Transformed cells show a low degree of connection. In the figure the network of predicted associations for all DEGs-encoded proteins in TF/T comparison is shown. The STRING analysis of the protein-protein interactions was performed to DEGs with fold change ≥2 in the comparison. (PDF)