A Rare Case of Richter Transformation to Both Clonally Unrelated and Clonally Related Diffuse Large B-Cell Lymphoma in the Same Patient.

Richter transformation (RT) is a rare sequelae of chronic lymphocytic leukemia (CLL)/small lymphocytic lymphoma (SLL). The clonal relationship of the RT to the underlined CLL/SLL is an important prognostic factor as clonally related RT has a worse prognosis than that of clonally unrelated RT. The development of more than one RT in the same patient is exceedingly rare and prior reports have shown cases consisting of RT to diffuse large B-cell lymphoma (DLBCL) and a subsequent or synchronous Hodgkin lymphoma. Here, we present a rare case of RT first to a clonally unrelated DLBCL and subsequently a clonally related DLBCL. Additionally, we retrospectively conducted next-generation sequencing studies of both RTs and found different mutational landscapes, including more clinically aggressive mutations identified in the clonally related RT. To our knowledge, this is the first reported case of clonally related and clonally unrelated RT, both of which are DLBCL, in the same patient

Neurofibromatosis Type 1 Implicates Ras Pathways in the Genetic Architecture of Neurodevelopmental Disorders

The genetic architecture of neurodevelopmental disorders is largely polygenic, non-specific, and pleiotropic. This complex genetic architecture makes the search for specific etiological mechanisms that contribute to neurodevelopmental risk more challenging. Monogenic disorders provide an opportunity to focus in on how well-articulated signaling pathways contribute to risk for neurodevelopmental outcomes. This paper will focus on neurofbromatosis type 1 (NF1), a rare monogenic disorder that is associated with varied neurodevelopmental outcomes. Specifically, this paper will provide a brief overview of NF1 and its phenotypic associations with autism spectrum disorder, attention-deficit/hyperactivity disorder, and specific learning disorders, describe how variation within the NF1 gene increases risk for neurodevelopmental disorders via altered Ras signaling, and provide future directions for NF1 research to help elucidate the genetic architecture of neurodevelopmental disorders in the general population

Fusion, 2022

https://hsrc.himmelfarb.gwu.edu/smhs_fusion/1014/thumbnail.jp

Spatial and temporal features of neutrophils in homeostasis from the perspective of computational biology

Tesis Doctoral inédita leída en la Universidad Autónoma de Madrid, Facultad de Ciencias, Departamento de Biología Molecular. Fecha de Lectura: 22-07-2022Neutrophils are myeloid cells that originate in the Bone Marrow and enter circulation to patrol for infectious agents. An important part of the “nonspecific” immune system consists on Neutrophils infiltrating challenged tissues, and the established belief was that they stay away from steady-state organs to avoid the risk of exposing them to their cytotoxic content. In the papers presented in this thesis, we show that neutrophils can in fact be found in almost all tissues under homeostasis. We further present proof that they undergo shifts in DNA accessibility, RNA expression and protein content in the infiltrated tissues. Using functional annotation we predict distinct roles depending on the tissue. While in hematopoietic organs the transcriptomic signatures of neutrophils align with canonical functions like immune response and migration, in other tissues such as the skin we find non-canonical functions i.e, epithelial and connective tissue growth or pro-angiogenic roles in the gut and the lung. This predicted pro-angiogenic role was indeed confirmed for the lung. We finally describe that infiltration in tissues follows circadian dynamics, and that once it has occurred, neutrophils experience changes in transcription depending on the time of the day. The analyses of circadian rhythms on mammalian models are often hindered by the inherent difficulty of performing exhaustive sampling (i.e.: every hour for at least 48h). Hence, I implemented CircaN as an R package, which outperforms existing tools in most scenarios. To provide the most complete analysis possible, we provide a full mode analysis option, in which we run CircaN and the two most used algorithms and provide integrated results. We present proof-of-concept results showing that combining various tools yields the best true positive to false positive ratio for most purposesEsta Tesis ha sido financiada por el Ministerio de Ciencia, Innovación y Universidades (MICINN

The combined strategy for iron uptake is not exclusive to domesticated rice

Iron (Fe) is an essential micronutrient that is frequently inaccessible to plants. Rice (Oryza sativa L.) plants employ the Combined Strategy for Fe uptake, which is composed by all features of Strategy II, common to all Poaceae species, and some features of Strategy I, common to non-Poaceae species. To understand the evolution of Fe uptake mechanisms, we analyzed the root transcriptomic response to Fe defciency in O. sativa and its wild progenitor O. rufpogon. We identifed 622 and 2,017 diferentially expressed genes in O. sativa and O. rufpogon, respectively. Among the genes up-regulated in both species, we found Fe transporters associated with Strategy I, such as IRT1, IRT2 and NRAMP1; and genes associated with Strategy II, such as YSL15 and IRO2. In order to evaluate the conservation of these Strategies among other Poaceae, we identifed the orthologs of these genes in nine species from the Oryza genus, maize and sorghum, and evaluated their expression profle in response to low Fe condition. Our results indicate that the Combined Strategy is not specifc to O. sativa as previously proposed, but also present in species of the Oryza genus closely related to domesticated rice, and originated around the same time the AA genome lineage within Oryza diversifed. Therefore, adaptation to Fe2+ acquisition via IRT1 in fooded soils precedes O. sativa domestication

Vineyard “Naturalness”: Principles and Challenges

The notion of "natural wines" has gained traction, yet the concept of vineyard naturalness remains largely neglected, often conflated with "organic" or "regenerative" viticulture. Vineyard naturalness, however, is rooted in a holistic approach that transcends these terms. In our effort to define its objectives, we focused on the methods and practices that enable its realization. This review explores several "natural-based" solutions aimed at the canopy and soil, guided by three core principles: (i) maximizing the use of freely available natural resources to reduce reliance on external and costly inputs; (ii) promoting approaches that support natural vine growth and productivity with minimal corrective interventions (repeated summer pruning serves as a prime example); and (iii) fostering practices that trigger natural tolerance responses to biotic or abiotic stresses. At the canopy level, the topics covered in this review include (i) strategies and tools to enhance light interception, distribution, and the conversion of assimilates into dry matter; (ii) leveraging existing biodiversity, including indigenous varieties and new rootstocks, to enhance adaptability to climate change challenges; and (iii) efforts to improve vineyard balance through the targeted application of established techniques, such as early basal leaf removal and late winter pruning, which can significantly enhance tolerance to biotic and abiotic stresses. On the soil front, our focus will be on (i) enhancing the green water footprint within a vineyard ecosystem; (ii) identifying the optimal combination to achieve a carbon sink function in the vineyard without excessive competition for water and nutrients from cover crops; and (iii) increasing the ecological value of cover cropping, exemplified by reducing the splash dispersal of fungal pathogens through the growth of a tall interrow cover crop in spring and its subsequent termination under a sub-row mulching solution. Moving toward vineyard naturalness does not imply reverting to the wild behavior of nondomesticated plants; rather, it involves maintaining a necessary remunerative yield at the desired grape quality while employing a range of physiologically robust solutions that minimize the need for constant corrections and amendments in vineyard management

Surviving starvation: proteomic and lipidomic profiling of nutrient deprivation in the smallest known free-living eukaryote

Marine phytoplankton, comprising cyanobacteria, micro- and pico-algae are key to photosynthesis, oxygen production and carbon assimilation on Earth. The unicellular green picoalga Ostreococcus tauri holds a key position at the base of the green lineage of plants, which makes it an interesting model organism. O. tauri has adapted to survive in low levels of nitrogen and phosphorus in the open ocean and also during rapid changes in the levels of these nutrients in coastal waters. In this study, we have employed untargeted proteomic and lipidomic strategies to investigate the molecular responses of O. tauri to low-nitrogen and low-phosphorus environments. In the absence of external nitrogen, there was an elevation in the expression of ammonia and urea transporter proteins together with an accumulation of triglycerides. In phosphate-limiting conditions, the expression levels of phosphokinases and phosphate transporters were increased, indicating an attempt to maximise scavenging opportunities as opposed to energy conservation conditions. The production of betaine lipids was also elevated, highlighting a shift away from phospholipid metabolism. This finding was supported by the putative identification of betaine synthase in O. tauri. This work offers additional perspectives on the complex strategies that underpin the adaptive processes of the smallest known free-living eukaryote to alterations in environmental conditions

From Pieces To Paths: Combining Disparate Information in Computational Analysis of RNA-Seq.

As high-throughput sequencing technology has advanced in recent decades, large-scale genomic data with high-resolution have been generated for solving various problems in many felds. One of the state-of-the-art sequencing techniques is RNA sequencing, which has been widely used to study the transcriptomes of biological systems through millions of reads. The ultimate goal of RNA sequencing bioinformatics algorithms is to maximally utilize the information stored in a large amount of pieced-together reads to unveil the whole landscape of biological function at the transcriptome level. Many bioinformatics methods and pipelines have been developed for better achieving this goal. However, one central question of RNA sequencing is the prediction uncertainty due to the short read length and the low sampling rate of underexpressed transcripts. Both conditions raise ambiguities in read mapping, transcript assembly, transcript quantifcation, and even the downstream analysis. This dissertation focuses on approaches to reducing the above uncertainty by incorporating additional information, of disparate kinds, into bioinformatics models and modeling assessments. I addressed three critical issues in RNA sequencing data analysis. (1) we evaluated the performance of current de novo assembly methods and their evaluation methods using the transcript information from a third generation sequencing platform, which provides a longer sequence length but with a higher error rate than next-generation sequencing; (2) we built a Bayesian graphical model for improving transcript quantifcation and di˙erentially expressed isoform identifcation by utilizing the shared information from biological replicates; (3) we built a joint pathway and gene selection model by incorporating pathway structures from an expert database. We conclude that the incorporation of appropriate information from extra resources enables a more reliable assessment and a higher prediction performance in RNA sequencing data analysis

Data-independent acquisition mass spectrometry for human gut microbiota metaproteome analysis

Human digestive tract microbiota is a diverse community of microorganisms having complex interactions between microbes and the human host. Observing the functions carried out by microbes is essential for gaining understanding on the role of gut microbiota in human health and associations to diseases. New methods and tools are needed for acquirement of functional information from complex microbial samples. Metagenomic approaches focus on taxonomy or gene based function potential but lack power in the discovery of the actual functions carried out by the microbes. Metaproteomic methods are required to uncover the functions. The current highthroughput metaproteomics methods are based on mass spectrometry which is capable of identifying and quantifying ionized protein fragments, called peptides. Proteins can be inferred from the peptides and the functions associated with protein expression can be determined by using protein databases. Currently the most widely used data-dependent acquisition (DDA) method records only the most intensive ions in a semi-stochastic manner, which reduces reproducibility and produces incomplete records impairing quantification. Alternative data-independent acquisition (DIA) systematically records all ions and has been proposed as a replacement for DDA. However, recording all ions produces highly convoluted spectra from multiple peptides and, for this reason, it has not been known if and how DIA can be applied to metaproteomics where the number of different peptides is high. This thesis work introduced the DIA method for metaproteomic data analysis. The method was shown to achieve high reproducibility enabling the usage of only a single analysis per sample while DDA requires multiple. An easy to use open source software package, DIAtools, was developed for the analysis. Finally, the DIA analysis method was applied to study human gut microbiota and carbohydrate-active enzymes expressed in members of gut microbiota.Ihmisen suolistomikrobiston analyysi DIAmassaspektrometriamenetelmällä Ihmisen suoliston mikrobisto on monien mikro-organismien yhteisö, joka on vuorovaikutuksessa ihmisen kehon kanssa. Suoliston mikrobien toiminnan ymmärtäminen on keskeistä niiden roolista ihmisen terveyteen ja sairauksiin. Uusia tutkimusmenetelmiä tarvitaan mikrobien toiminnallisuuden määrittämiseen monimutkaisista, useita mikrobeja sisältävistä, näytteistä. Yleisesti käytetyt metagenomiikan menetelmät keskittyvät taksonomiaan tai geenien perusteella ennustettuihin funktioihin, mutta metaproteomiikkaa tarvitaan mikrobien toiminnan selvittämiseen. Metaproteomiikka-analyysiin voidaan käyttää massaspektrometriaa, jolla pystytään tunnistamaan ja määrittämään ionisoitujen proteiinien osasten, peptidien, määrä. Proteiinit voidaan päätellä peptideistä ja näin pystytään määrittämään proteiineihin liittyviä toimintoja hyödyntäen proteiinitietokantoja. Nykyisin käytetty DDA-menetelmä tunnistaa vain runsaimmin esiintyvät ionit, mikä rajoittaa sen hyödyntämistä. Siinä mitattavien ionien valinta on jossain määrin satunnainen, mikä vähentää tulosten toistettavuutta. Vaihtoehtoinen DIA-menetelmä analysoi järjestelmällisesti kaikki ionit ja kyseistä menetelmää on ehdotettu DDA:n tilalle. DIA-menetelmä tuottaa päällekkäisiä peptidispektrejä ja siksi aiemmin ei ole ollut tiedossa, onko se soveltuva menetelmä tai miten sitä olisi mahdollista soveltaa metaproteomiikkaan, jossa on suuri määrä erilaisia peptidejä. Tämä tutkimus esittelee soveltuvia tapoja DIA-menetelmän käyttöön metaproteomiikkadatan analysoinnissa. Työssä osoitetaan, että DIA-metaproteomiikka tuottaa luotettavasti toistettavia tuloksia. DIA-menetelmää käyttäessä riittää, että näyte analysoidaan vain yhden kerran, kun vastaavasti DDA-menetelmän käyttö vaatii useamman analysointikerran. Tutkimuksessa kehitettiin avoimen lähdekoodin ohjelmisto DIAtools, joka toteuttaa kehitetyt DIA-datojen analysointimenetelmät. Lopuksi DIA-analyysiä sovellettiin ruoansulatuskanavan mikrobien ja niiden tuottamien CAZy-entsyymien tutkimiseksi