26S PROTEASOME AND PKA MODULATE MAMMALIAN SPERM CAPACITATION BY CREATING AN INTEGRATED DIALOGUE: A COMPUTATIONAL ANALYSIS

Recent experimental evidence suggests the involvement of the 26S proteasome, the main protease active in eukaryotic cells, in the process that leads mammalian sperm to become fully fertile, so-called capacitation. Unfortunately, its role in male gametes signaling is still far from being completely understood. For this reason, here, we realized a computational model as an attempt to rebuild and explore 26S proteasome signaling cascade, aggregating all the molecular data available to date and realizing the Proteasome Interactome Network (PIN). Once obtained the network (i.e., a graph to represent the molecules as nodes and the interactions among them as links), we assessed its topology to infer important biological information. PIN is composed of 157 nodes, 248 links and it is characterized by a scale-free topology, following the Barabasi Albert model. In other words, it possesses a large amount of scarcely linked nodes and a small set of highly linked nodes, the hubs, which act as system controllers. This peculiar topology confers to the network relevant biological features: it is robust against random attacks, easily navigable and controllable and it is possible to infer new information from it. Indeed, the analysis of PIN showed that PKA and 26S proteasome were strongly interconnected and both were active in sperm signaling by influencing the protein phosphorylation pattern and then controlling several key events in sperm capacitation, such as membrane and cytoskeleton remodeling. In conclusion, the network model could explain many biological aspects of sperm physiology that are out of focus looking at the single molecular determinant, overcoming the reductionist approach which did not consider the complexity of molecules and their interactions. This could be helpful to identify potential diagnostic markers and therapeutic strategies concurring in explaining and approaching male infertility

Clinically relevant radioresistant rhabdomyosarcoma cell lines: Functional, molecular and immune-related characterization

Background: The probability of local tumor control after radiotherapy (RT) remains still miserably poor in pediatric rhabdomyosarcoma (RMS). Thus, understanding the molecular mechanisms responsible of tumor relapse is essential to identify personalized RT-based strategies. Contrary to what has been done so far, a correct characterization of cellular radioresistance should be performed comparing radioresistant and radiosensitive cells with the same isogenic background. Methods: Clinically relevant radioresistant (RR) embryonal (RD) and alveolar (RH30) RMS cell lines have been developed by irradiating them with clinical-like hypo-fractionated schedule. RMS-RR cells were compared to parental isogenic counterpart (RMS-PR) and studied following the radiobiological concept of the "6Rs", which stand for repair, redistribution, repopulation, reoxygenation, intrinsic radioresistance and radio-immuno-biology. Results: RMS-RR cell lines, characterized by a more aggressive and in vitro pro-metastatic phenotype, showed a higher ability to i) detoxify from reactive oxygen species; ii) repair DNA damage by differently activating non-homologous end joining and homologous recombination pathways; iii) counteract RT-induced G2/M cell cycle arrest by re-starting growth and repopulating after irradiation; iv) express cancer stem-like profile. Bioinformatic analyses, performed to assess the role of 41 cytokines after RT exposure and their network interactions, suggested TGF-β, MIF, CCL2, CXCL5, CXCL8 and CXCL12 as master regulators of cancer immune escape in RMS tumors. Conclusions: These results suggest that RMS could sustain intrinsic and acquire radioresistance by different mechanisms and indicate potential targets for future combined radiosensitizing strategies

La biologia computazionale a servizio del linfoma canino: nuovi orizzonti?

Scopo del lavoro - Il linfoma è uno dei tumori più frequenti nel cane, rappresentando circa il 7-24% di tutte le neoplasie e oltre l’80% delle neoplasie ematologiche. Origina dal tessuto linfoide (linfonodi, milza, midollo) e può estendersi a tutti gli organi e tessuti dell’organismo ed in genere colpisce cani di mezza età o di età avanzata. Attualmente sono descritti almeno cinque diver- si tipi più frequenti di linfoma canino (LC): multicentrico, mediastinico, gastrointestinale, extra-nodale e del sistema nervoso centrale1. La sua eziologia non è nota ed è ritenuta essere una patologia multifattoriale. In particolare sono state riscontrate aber- razioni cromosomiche, il coinvolgimento di retrovirus e cause ambientali (erbicidi, solventi, inquinamento industriale). La pato- genesi rimane in gran parte ignota2. In questo contesto, abbiamo utilizzato innovative metodiche di biomedical text mining (o Biomedical Informatics Natural Lan- guage Processing, BioNLP) e di modellistica computazionale per identificare le proteine coinvolte nel LC, sia per chiarirne i meccanismi patogenetici che, potenzialmente, per proporre possibili targets terapeutici e/o markers diagnostici. In particolare: 1) mediante l’uso del BioNLP è stata ottenuta una lista di proteine coinvolte nell’eziopatogenesi del LC accedendo alle conoscenze contenute nel testo nascosto e non strutturato (hidden and unstructured text) presente negli articoli indiciz- zati su PubMed (http://www.ncbi.nlm.nih.gov/pubmed)3. In tal modo è stato possibile implementare le conoscenze ad oggi disponibili; 2) è stato costruito un modello computazionale basato sulla teoria delle reti biologiche (biological networks) con le molecole coinvolte (nodi della rete) e le loro interazioni (links tra i nodi)3; 3) l’analisi della topologia della rete ha consentito di identificare le molecole caratterizzate da un più elevato grado di control- lo sulla rete stessa, ovvero quelle che verosimilmente possono essere ottimi candidati come markers diagnostici e/o target terapeutici4,5. Materiali e metodi - Per il BioNLP è stato usato il software Agilent Literature Search 3.1.1 (LitSearch version 2.6.9). L’ac- cesso ai dati è stato realizzato tra il 2 ed il 4 febbraio 2015. Una volta ottenuta la lista di proteine coinvolte, è stata condotta un’analisi per definirne le interazioni mediante il software STRING (Search Tool for the Retrieval of Interacting Genes/Proteins, http://string-db.org/). La rete formata dalle proteine (nodi) e dalle loro interazioni (links) è stata realizzata e visualizzata mediante Cytoscape 3.2.1, la topologia è stata analizzata con plug-in Network Analyzer (http://med.bioinf. mpi-inf. mpg.de/netanalyzer/index.php)6,7. Risultati - La ricerca mediante BioNLP ha consentito di identificare una lista di 79 proteine coinvolte nell’eziopatogenesi del linfoma canino. L’analisi su STRING ha permesso di definire le loro interazioni per creare, con Cytoscape, una rete composta da 31 connected components, 554 nodi e 1614 links. L’analisi della rete (trattata come non diretta) ha permesso di classificarla come rete ad invarianza di scala (node degree distribution: y=370.18 x-1.629, r=0.663, R2=0.762) di tipo gerarchico (clustering coefficient =0.621, Averaged Clustering Coefficent vs. Number of Neighbors: y=1.932 x-0.629, r=0.915, R2=0.908). Proprio grazie a tale topologia è stato possibile identificare i nodi col maggior numero di links, gli hubs del sistema, che dimostrano anche un elevato grado di centralità nella rete (node degree vs. betweenness centrality r=0.676 e vs. closeness centrality r=0.677). Tali proteine sono elencate, in ordine decrescente di controllo, qui di seguito: c-jun: insieme a c-fos coinvolto nel controllo del ciclo cellulare e nella regolazione dell’apoptosi. p53: un fattore di trascrizione che regola il ciclo cellulare e ricopre la funzione di soppressore tumorale. Grb2: un adaptor protein coinvolto nella trasduzione del segnale e nella comunicazione fra cellule; in particolare lega il recet- tore per EGF. PIK3CB: fosfoinositide 3-chinasi, subunità catalitica beta, coinvolta in varie vie di trasduzione del segnale che regolano la cre- scita cellulare in risposta a vari stimoli mitotici. LYN: appartiene alla famiglia delle proteinchinasi Src ed espresso principalmente da cellule ematopoietiche, tessuto nervoso, fegato e tessuto adiposo; in particolare nelle cellule emopoietiche è uno degli enzimi chiave coinvolti nella regolazione dell’at- tivazione cellulare. PIK3R1: fosfatidilinositolo-3-chinasi, ha un importante ruolo nell’azione dell’insulina. AKT1: attivata dalla fosfatidilinositolo-3-chinasi, i ratti KO per il gene Akt1 sono resistenti ai tumori. PTPN6: coinvolta nella differenziazione cellulare, ciclo mitotico e trasformazione oncogena. c-fos: vedi c-jun. Conclusioni - Grazie all’uso di sofisticate metodiche computazionali è possibile individuare nuove proteine coinvolte nell’e- ziopatogenesi del LC, che potrebbero rappresentare futuri markers diagnostici e/o targets terapeutici

Network Analyses of Sperm–Egg Recognition and Binding: Ready to Rethink Fertility Mechanisms?

The rapid growth of published literature makes biomedical text mining increasingly invaluable for unpacking implicit knowledge hidden in unstructured text. We employed biomedical text mining and biological networks analyses to research the process of sperm egg recognition and binding (SERB). We selected from the literature the molecules expressed either on spermatozoa or on oocytes thought to be involved in SERB and, using an automated literature search software (Agilent Literature Search), we realized a network, SERBN, characterized by a hierarchical scale free and a small world topology. We used an integrated approach, either based on selection of hubs or by a cluster analysis, to discern the key molecules of SERB. We found that in most cases some of them are not directly situated on spermatozoa and oocyte, but are dispersed in oviductal fluid or embedded in exosomes present in the perivitelline space. To confirm and validate our results, we performed further analyses using STRING and Reactome FI software. Our findings underscore that the fertility is not a property of gametes in isolation, but rather depends on the functional integrity of the entire reproductive system. These observations collectively underscore the importance of integrative biology in exploring biological systems and in rethinking of fertility mechanisms in the light of this innovative approach

Cyclin-CDK Complexes are Key Controllers of Capacitation-Dependent Actin Dynamics in Mammalian Spermatozoa

Mammalian spermatozoa are infertile immediately after ejaculation and need to undergo a functional maturation process to acquire the competence to fertilize the female egg. During this process, called capacitation, the actin cytoskeleton dramatically changes its organization. First, actin fibers polymerize, forming a network over the anterior part of the sperm cells head, and then it rapidly depolymerizes and disappears during the exocytosis of the acrosome content (the acrosome reaction (AR)). Here, we developed a computational model representing the actin dynamics (AD) process on mature spermatozoa. In particular, we represented all the molecular events known to be involved in AD as a network of nodes linked by edges (the interactions). After the network enrichment, using an online resource (STRING), we carried out the statistical analysis on its topology, identifying the controllers of the system and validating them in an experiment of targeted versus random attack to the network. Interestingly, among them, we found that cyclin-dependent kinase (cyclin-CDK) complexes are acting as stronger controllers. This finding is of great interest since it suggests the key role that cyclin-CDK complexes could play in controlling AD during sperm capacitation, leading us to propose a new and interesting non-genomic role for these molecules