Computational solutions for omics data

High-throughput experimental technologies are generating increasingly massive and complex genomic data sets. The sheer enormity and heterogeneity of these data threaten to make the arising problems computationally infeasible. Fortunately, powerful algorithmic techniques lead to software that can answer important biomedical questions in practice. In this Review, we sample the algorithmic landscape, focusing on state-of-the-art techniques, the understanding of which will aid the bench biologist in analysing omics data. We spotlight specific examples that have facilitated and enriched analyses of sequence, transcriptomic and network data sets.National Institutes of Health (U.S.) (Grant GM081871

Microbial Changes in Gene Expression Level in Response to Environmental Conditions in the Delaware Bay

Bacteria dominate in abundance, diversity and potentially metabolic activity in many environments. Our current knowledge on the influence of specific individual taxa on these processes is largely lacking. To bridge these gaps, I chose three near complete metagenome-assembled genomes (MAGs) from the Delaware Bay, phylogenetically associated with the Roseobacter clade, to compare the functional potential of the MAGs to their closest relatives. I also characterized the relative activity of one MAG by using normalized gene expression levels and differential gene expression. The normalized number of transcripts per sample revealed whether or not specific genes/pathways were being expressed at the time of sampling. In all of the different conditions that the samples were collected from, a high number of transcripts related to membrane transporters, energy metabolism and ribosomal proteins were observed for MAG 22. Differential expression was observed between environmental conditions including season, time of day and salinity. For differential gene expression, the significantly up or down regulation of gene transcription between environmental conditions was characterized to visualize any patterns in metabolism. My overall results indicate that the organism remains active throughout the year, however, the types of physiology it utilizes changes based on the conditions present

Sensing and molecular communication using synthetic cells: Theory and algorithms

Molecular communication (MC) is a novel communication paradigm in which molecules are used to encode, transmit and decode information. MC is the primary method by which biological entities exchange information and hence, cooperate with each other. MC is a promising paradigm to enable communication between nano-bio machines, e.g., biosensors with potential applications such as cancer and disease detection, smart drug delivery, toxicity detection etc. The objective of this research is to establish the fundamentals of diffusion-based molecular communication and sensing via biological agents (e.g., synthetic bacteria) from a communication and information theory perspective, and design algorithms for reliable communication and sensing systems. In the first part of the thesis, we develop models for the diffusion channel as well as the molecular sensing at the receiver and obtain the maximum achievable rate for such a communication system. Next, we study reliability in MC. We design practical nodes by employing synthetic bacteria as the basic element of a biologically-compatible communication system and show how reliable nodes can be formed out of the collective behavior of a population of unreliable bio-agents. We model the probabilistic behavior of bacteria, obtain the node sensing capacity and propose a practical modulation scheme. In order to improve the reliability, we also introduce relaying and error-detecting codes for MC. In the second part of the thesis, we study the molecular sensing problem with potential applications in disease detection. We establish the rate-distortion theory for molecular sensing and investigate as to how distortion can be minimized via an optimal quantizer. We also study sensor cell arrays in which sensing redundancy is achieved by using multiple sensors to measure several molecular inputs simultaneously. We study the interference in sensing molecular inputs and propose a probabilistic message passing algorithm to solve the pattern detection over the molecular inputs of interest.Ph.D

Training Manual ICAR Short course on Application of advanced molecular methods in marine fishery resource management, conservation and sustainable mariculture

Molecular Biology and Biotechnology has undergone incredible progress in this decade mainly due to the rapid advancements in DNA sequencing technologies. Marine biology and fishery science also reaped the fruits of these modern inventions improving our understanding regarding complex adaptations in aquatic organisms. Fish Genetics have evolved into genomics incorporating knowledge about neutral and non-neutral markers. A project called Genome 10k was started by the international community of scientists for sequencing the genome of 10000 vertebrates. Whole genomes of many marine organisms are now available which provided insights into the evolution of many important traits. Transcriptome sequencing provides insights into expressed genes and metagenome sequencing provides information regarding the microbes present in environment. All these technologies are rapid and cost effective. Over years, these technologies provided exciting opportunities for understanding ecology and evolution. Genomic information can also be sustainably utilized to enhance productivity of mariculture activities by selective breeding, genetic improvement and manipulation of economically important traits. ICAR-Central Marine Fisheries Research Institute has contributed significantly to marine biotechnology research in the country and played a pivotal role in development of marine fisheries sector. The short course on “Application of advanced molecular methods in marine fisheries resource management, conservation and sustainable mariculture” conducted in ICAR-CMFRI from 24th October, 2018 to 2nd November, 2018 is specially designed to provide exposure to various applications of molecular tools in fisheries resource management, conservation of biodiversity and mariculture. I hope this compendium of lectures and protocols will be extremely useful for the participants to effectively utilize the knowledge in their own area of research. Simultaneously, on behalf of ICAR-CMFRI, I warmly welcome all the participants from various institutions and wish them all success in their future endeavors. I am sure that this training will result in new knowledge, collaborations and friendships

Bifidobacteria on the spot: a genomics approach on population dynamaics and interactions in the intestinal tract

This thesis combines comprehensive microarray-based studies contributing to a better understanding of the role of bifidobacteria in relation to the human host. It reviews recently described modes of interaction between bifidobacteria and human gastrointestinal cells and highlights the unique characteristics of the genus Bifidobacterium that are indicative for its role in our gut. A microarray platform has been developed that enables genomic comparison of Bifidobacterium species originating from our gastrointestinal tract (GIT). Based on the obtained high-resolution data, species-unique genomic sequences could be identified. A large fraction of these predicted genes encode proteins belonging to the bifidobacterial glycobiome. An unique ability of the microarray platform is to zoom in on the strain level. Direct mapping of genomic hybridization patterns was applied on different B. breve isolates. This revealed a relatively high genomic variation, testifying for the existence of various subspecies within the species B. breve. Clustering of the same hybridization patterns resulted in clear grouping of isolates originating from the same infant, indicating specific niche adaption. Additionally, DNA extracts from Bifidobacterium populations from different infant fecal samples were analyzed. This enabled the analysis of the bifidobacterial population dynamics in breast- and formula-fed infants. The applied microarray platform showed the potential to monitor temporal development and effects of dietary regimens. The observed differences in the composition of bifidobacterial populations could be linked to dietary effects. Additionally, mapping of hybridization patterns enabled monitoring shifts in genomic content within one bifidobacterial species in time. Sequence analysis of DNA fragments showing discriminating hybridization characteristics, resulted in the selection of genes that are either conserved or strain-specific within the species B. breve. Next to studying genomic variation, transcript profiling experiments in both bifidobacterial cells and human intestinal epithelial cell lines were performed. Analysis of bifidobacterial transcriptional responses provided clear proof of transcriptional activity in bifidobacterial cells isolated from infant feces. To the best of our knowledge, this is the first demonstration of in situ activity of bifidobacteria in the human GIT. Furthermore, our results indicate a link between transcription patterns and the infants’ diet, as bifidobacteria in fecal samples from breast-fed infants showed differential transcriptional responses in comparison to those in fecal samples from formula-fed infants. Additionally, transcript sequence analysis revealed expression of genes that are homologous to genes known to be involved in folate production, testifying for the production of this important vitamin in early life. Finally, transcriptome analysis on human intestinal epithelial cells (HIECs) showed species-specific suppression by B. breve M-16V of genes upregulated by TNF-α. Other B. breve strains showed an extreme mild or no effect on TNF-α stimulation. Although we did not observe complete suppression of the TNF effect, we could show that apoptotic and immune regulatory pathways were affected by incubation with cells of B. breve M-16V. In conclusion, the work presented in the thesis, which formed part of a larger IOP Genomics project, contributed to an advanced insight in the interaction between bifidobacteria and the human host. Furthermore, it resulted in the development of genome-based molecular platforms suited for analyzing genomic diversity between and within species, as well as population dynamics in complex microbial communities. We anticipate that the molecular approaches pioneered in this thesis will be instrumental in the further elucidation of the host-microbe interactions in the GIT of human an other animals. <br/

Bioinformatic analysis of genome-scale data reveals insights into host-pathogen interactions in farm animals

This thesis documents the contribution of my bioinformatics research activities, including novel software development, to a range of research projects aimed at investigating the interactions between bacterial and viral pathogens and their hosts. The focus is largely on farm animal species and their pathogens, although some of the research has a wider scientific impact. RNA interference (RNAi) refers to a variety of related regulatory pathways present in animals, plants and insects. The major pathways are microRNAs (miRNAs), small-interfering RNAs (siRNAs) and PIWI-interacting RNAs (piRNAs). Marek’s disease virus is an important pathogen of poultry, causing T-cell lymphoma. We identified the presence and expression patterns of several MDV-encoded microRNAs, including the identification of 5 novel microRNAs. We also showed that not only do virus-encoded microRNAs dominate the mirNome within chicken cells, but also that specific host-microRNAs are down-regulated. We also identify novel virus-encoded microRNAs in other Herpesviridae and provide the first evidence of miRNA evolution by duplication in viruses. In related work, we present a novel microRNA generated by the canonical miRNA biogenesis pathway in Avian Leukosis Virus, another avian oncogenic virus, and publish data showing the expression pattern of known chicken microRNAs across a range of important avian cells. Two of the other RNAi pathways (siRNA and piRNA) form an important part of the antiviral response in arthropods. We have published work demonstrating an siRNA antiviral response to bluetongue virus and Schmallenberg virus in cells from the Culicoides midge, an important insect vector, as well as work demonstrating the importance of the piRNA pathway in the antiviral response to Semliki forest virus (SFV). Further work on flaviviruses in ticks demonstrates the active suppression of the siRNA response by Langat Virus, as well as a key difference between the siRNA responses in Mosquitos compared to ticks. Salmonella is one of the most important zoonoses, with an estimated 1.4 million cases of human salmonellosis per annum in the USA alone. Salmonella infections of farm animals are an important route into the human food chain. This thesis presents work on the comparative structure and function of 13 fimbrial operons within Salmonella enterica serovar Enteritidis as well as a genomic comparison of that serovar with Salmonella enterica serovar Gallinarum, a chicken-specific serovar. We characterised the global expression profile of Salmonella enterica serovar Typhimurium during colonization of the chicken intestine, and we have published the genomes of four strains of Salmonella eneterica serovars of well-defined virulence in food-producing animals. Our work in this area led to us publishing an important and comprehensive review of the automatic annotation of bacterial genomes. Finally, I present work on novel software development. ProGenExpress, a software tool that allows the easy and accurate integration and visualisation of quantitative data with the genome annotation of bacteria; Meta4 is a web application that allows data sharing of bacterial genome annotations from metagenomes; CORNA, a software tool that allows scientists to link together microRNA targets, gene expression and functional annotation; viRome, a software tool for the analysis of siRNA and piRNA responses in virus-infection studies; DetectiV, a software tool for the analysis of pathogen-detection microarray data; and poRe, a software tool that enables users to organise and analyse nanopore sequencing dat

Investigation of the gallbladder host environment and small RNAs in the pathobiology of Campylobacter jejuni sheep abortion clone IA 3902

Campylobacter jejuni is an important zoonotic agent that is the leading cause of both human foodborne bacterial gastroenteritis worldwide, as well as ovine abortion in the United States. In particular, a single C. jejuni sheep abortion clone, of which IA 3902 is a prototypical isolate, has recently emerged as the dominant causative agent of sheep abortion due to Campylobacter sp. in the U.S. and has been increasingly identified in human outbreaks of disease. Multi-omics approaches to studying this hypervirulent strain have shown that it is remarkably similar to other common strains of C. jejuni such as 11168 that do not show the same ability to cause systemic clinical disease. Further work to elucidate the molecular mechanisms that allow for small changes in genomic structure to lead to large changes in virulence ability in this important zoonotic agent is warranted. A number of studies have demonstrated that the gallbladder of ruminants, as well as other domestic animal species, is often positive on culture for Campylobacter sp. following oral exposure, suggesting that this environment may serve as a chronic nidus of infection for maintenance of disease within populations. By utilizing a unique in vivo model of gallbladder infection, the work conducted within this dissertation has allowed identification of the preferred location of C. jejuni IA 3902 within the gallbladder host environment as well as demonstrated putative host factors that may play a role in its localization to that site. In addition, by utilizing emerging RNA sequencing technology, we were able to determine numerous protein coding genes and non-coding RNAs that were differentially expressed following exposure to the in vivo gallbladder host environment. One of these identified non-coding RNAs, CjNC110, was selected for further study. Inactivation of the CjNC110 non-coding RNA in IA 3902 allowed us for the first time to identify transcriptomic and phenotypic changes associated with loss of function of a small RNA in any species of Campylobacter. The collective results of these experiments provide additional evidence to begin to elucidate the role of gallbladder colonization and small RNAs in the pathobiology of the important zoonotic pathogen, C. jejuni IA 3902

From tools and databases to clinically relevant applications in miRNA research

While especially early research focused on the small portion of the human genome that encodes proteins, it became apparent that molecules responsible for many key functions were also encoded in the remaining regions. Originally, non-coding RNAs, i.e., molecules that are not translated into proteins, were thought to be composed of only two classes (ribosomal RNAs and transfer RNAs). However, starting from the early 1980s many other non-coding RNA classes were discovered. In the past two decades, small non-coding RNAs (sncRNAs) and in particular microRNAs (miRNAs), have become essential molecules in biological and biomedical research. In this thesis, five aspects of miRNA research have been addressed. Starting from the development of advanced computational software to analyze miRNA data (1), an in-depth understanding of human and non-human miRNAs was generated and databases hosting this knowledge were created (2). In addition, the effects of technological advances were evaluated (3). We also contributed to the understanding on how miRNAs act in an orchestrated manner to target human genes (4). Finally, based on the insights gained from the tools and resources of the mentioned aspects we evaluated the suitability of miRNAs as biomarkers (5). With the establishment of next-generation sequencing, the primary goal of this thesis was the creation of an advanced bioinformatics analysis pipeline for high-throughput miRNA sequencing data, primarily focused on human. Consequently, miRMaster, a web-based software solution to analyze hundreds sequencing samples within few hours was implemented. The tool was implemented in a way that it could support different sequencing technologies and library preparation techniques. This flexibility allowed miRMaster to build a consequent user-base, resulting in over 120,000 processed samples and 1,5 billion processed reads, as of July 2021, and therefore laid out the basis for the second goal of this thesis. Indeed, the implementation of a feature allowing users to share their uploaded data contributed strongly to the generation of a detailed annotation of the human small non-coding transcriptome. This annotation was integrated into a new miRNA database, miRCarta, modelling thousands of miRNA candidates and corresponding read expression profiles. A subset of these candidates was then evaluated in the context of different diseases and validated. The thereby gained knowledge was subsequently used to validate additional miRNA candidates and to generate an estimate of the number of miRNAs in human. The large collection of samples, gathered over many years with miRMaster was also integrated into a web server evaluating miRNA arm shifts and switches, miRSwitch. Finally, we published an updated version of miRMaster, expanding its scope to other species and adding additional downstream analysis capabilities. The second goal of this thesis was further pursued by investigating the distribution of miRNAs across different human tissues and body fluids, as well as the variability of miRNA profiles over the four seasons of the year. Furthermore, small non-coding RNAs in zoo animals were examined and a tissue atlas of small non-coding RNAs for mice was generated. The third goal, the assessment of technological advances, was addressed by evaluating the new combinatorial probe-anchor synthesis-based sequencing technology published by BGI, analyzing the effect of RNA integrity on sequencing data, analyzing low-input library preparation protocols, and comparing template-switch based library preparation protocols to ligation-based ones. In addition, an antibody-based labeling sequencing chemistry, CoolMPS, was investigated. Deriving an understanding of the orchestrated regulation by miRNAs, the fourth goal of this thesis, was pursued in a first step by the implementation of a web server visualizing miRNA-gene interaction networks, miRTargetLink. Subsequently, miRPathDB, a database incorporating pathways affected by miRNAs and their targets was implemented, as well as miEAA 2.0, a web server offering quick miRNA set enrichment analyses in over 130,000 categories spanning 10 different species. In addition, miRSNPdb, a database evaluating the effects of single nucleotide polymorphisms and variants in miRNAs or in their target genes was created. Finally, the fifth goal of the thesis, the evaluation of the suitability of miRNAs as biomarkers for human diseases was tackled by investigating the expression profiles of miRNAs with machine learning. An Alzheimer's disease cohort with over 400 individuals was analyzed, as well as another neurodegenerative disease cohort with multiple time points of Parkinson's disease patients and healthy controls. Furthermore, a lung cancer cohort covering 3,000 individuals was examined to evaluate the suitability of an early detection test. In addition, we evaluated the expression profile changes induced by aging on a cohort of 1,334 healthy individuals and over 3,000 diseased patients. Altogether, the herein described tools, databases and research papers present valuable advances and insights into the miRNA research field and have been used and cited by the research community over 2,000 times as of July 2021.Während insbesondere die frühe Genetik-Forschung sich auf den kleinen Teil des menschlichen Genoms konzentrierte, der für Proteine kodiert, wurde deutlich, dass auch in den übrigen Regionen Moleküle kodiert werden, die für viele wichtige Funktionen verantwortlich sind. Ursprünglich ging man davon aus, dass nicht codierende RNAs, d. h. Moleküle, die nicht in Proteine übersetzt werden, nur aus zwei Klassen bestehen (ribosomale RNAs und Transfer-RNAs). Seit den frühen 1980er Jahren wurden jedoch viele andere nicht-kodierende RNA-Klassen entdeckt. In den letzten zwei Jahrzehnten sind kleine nichtcodierende RNAs (sncRNAs) und insbesondere microRNAs (miRNAs) zu wichtigen Molekülen in der biologischen und biomedizinischen Forschung geworden. In dieser Arbeit werden fünf Aspekte der miRNA-Forschung behandelt. Ausgehend von der Entwicklung fortschrittlicher Computersoftware zur Analyse von miRNA-Daten (1) wurde ein tiefgreifendes Verständnis menschlicher und nicht-menschlicher miRNAs entwickelt und Datenbanken mit diesem Wissen erstellt (2). Darüber hinaus wurden die Auswirkungen des technologischen Fortschritts bewertet (3). Wir haben auch dazu beigetragen, zu verstehen, wie miRNAs koordiniert agieren, um menschliche Gene zu regulieren (4). Schließlich bewerteten wir anhand der Erkenntnisse, die wir mit den Tools und Ressourcen der genannten Aspekte gewonnen hatten, die Eignung von miRNAs als Biomarker (5). Mit der Etablierung der Sequenzierung der nächsten Generation war das primäre Ziel dieser Arbeit die Schaffung einer fortschrittlichen bioinformatischen Analysepipeline für Hochdurchsatz-MiRNA-Sequenzierungsdaten, die sich in erster Linie auf den Menschen konzentriert. Daher wurde miRMaster, eine webbasierte Softwarelösung zur Analyse von Hunderten von Sequenzierproben innerhalb weniger Stunden, implementiert. Das Tool wurde so implementiert, dass es verschiedene Sequenzierungstechnologien und Bibliotheksvorbereitungstechniken unterstützen kann. Diese Flexibilität ermöglichte es miRMaster, eine konsequente Nutzerbasis aufzubauen, die im Juli 2021 über 120.000 verarbeitete Proben und 1,5 Milliarden verarbeitete Reads umfasste, womit die Grundlage für das zweite Ziel dieser Arbeit geschaffen wurde. Die Implementierung einer Funktion, die es den Nutzern ermöglicht, ihre hochgeladenen Daten mit anderen zu teilen, trug wesentlich zur Erstellung einer detaillierten Annotation des menschlichen kleinen nicht-kodierenden Transkriptoms bei. Diese Annotation wurde in eine neue miRNA-Datenbank, miRCarta, integriert, die Tausende von miRNA-Kandidaten und entsprechende Expressionsprofile abbildet. Eine Teilmenge dieser Kandidaten wurde dann im Zusammenhang mit verschiedenen Krankheiten bewertet und validiert. Die so gewonnenen Erkenntnisse wurden anschließend genutzt, um weitere miRNA-Kandidaten zu validieren und eine Schätzung der Anzahl der miRNAs im Menschen vorzunehmen. Die große Sammlung von Proben, die über viele Jahre mit miRMaster gesammelt wurde, wurde auch in einen Webserver integriert, der miRNA-Armverschiebungen und -Wechsel auswertet, miRSwitch. Schließlich haben wir eine aktualisierte Version von miRMaster veröffentlicht, die den Anwendungsbereich auf andere Spezies ausweitet und zusätzliche Downstream-Analysefunktionen hinzufügt. Das zweite Ziel dieser Arbeit wurde weiterverfolgt, indem die Verteilung von miRNAs in verschiedenen menschlichen Geweben und Körperflüssigkeiten sowie die Variabilität der miRNA-Profile über die vier Jahreszeiten hinweg untersucht wurde. Darüber hinaus wurden kleine nichtkodierende RNAs in Zootieren untersucht und ein Gewebeatlas der kleinen nichtkodierenden RNAs für Mäuse erstellt. Das dritte Ziel, die Einschätzung des technologischen Fortschritts, wurde angegangen, indem die neue kombinatorische Sonden-Anker-Synthese-basierte Sequenzierungstechnologie, die vom BGI veröffentlicht wurde, bewertet wurde, die Auswirkungen der RNA-Integrität auf die Sequenzierungsdaten analysiert wurden, Protokolle für die Bibliotheksvorbereitung mit geringem Input analysiert wurden und Protokolle für die Bibliotheksvorbereitung auf der Basis von Template-Switch mit solchen auf Ligationsbasis verglichen wurden. Darüber hinaus wurde eine auf Antikörpern basierende Labeling-Sequenzierungschemie, CoolMPS, untersucht. Das vierte Ziel dieser Arbeit, das Verständnis der orchestrierten Regulation durch miRNAs, wurde in einem ersten Schritt durch die Implementierung eines Webservers zur Visualisierung von miRNA-Gen-Interaktionsnetzwerken, miRTargetLink, verfolgt. Anschließend wurde miRPathDB implementiert, eine Datenbank, die von miRNAs und ihren Zielgenen beeinflusste Pfade enthält, sowie miEAA 2.0, ein Webserver, der schnelle miRNA-Anreicherungsanalysen in über 130.000 Kategorien aus 10 verschiedenen Spezies bietet. Darüber hinaus wurde miRSNPdb, eine Datenbank zur Bewertung der Auswirkungen von Einzelnukleotid-Polymorphismen und Varianten in miRNAs oder ihren Zielgenen, erstellt. Schließlich wurde das fünfte Ziel der Arbeit, die Bewertung der Eignung von miRNAs als Biomarker für menschliche Krankheiten, durch die Untersuchung der Expressionsprofile von miRNAs anhand von maschinellem Lernen angegangen. Eine Alzheimer-Kohorte mit über 400 Personen wurde analysiert, ebenso wie eine weitere neurodegenerative Krankheitskohorte mit Parkinson-Patienten an mehreren Zeitpunkten der Krankheit und gesunden Kontrollen. Außerdem wurde eine Lungenkrebskohorte mit 3.000 Personen untersucht, um die Eignung eines Früherkennungstests zu bewerten. Darüber hinaus haben wir die altersbedingten Veränderungen des Expressionsprofils bei einer Kohorte von 1.334 gesunden Personen und über 3.000 kranken Patienten untersucht. Insgesamt stellen die hier beschriebenen Tools, Datenbanken und Forschungsarbeiten wertvolle Fortschritte und Erkenntnisse auf dem Gebiet der miRNA-Forschung dar und wurden bis Juli 2021 von der Forschungsgemeinschaft über 2.000 Mal verwendet und zitiert

Genomic and metagenomic approaches to natural product chemistry

For many years, natural products have been a primary source of new molecules for the treatment of disease, and microorganisms have been a prolific source of these molecules. Recent studies have indicated, however, that many biosynthetic pathways are present in organisms for which no natural product can be associated, and only a small fraction of the microbial life present in the environment can be grown in culture. This indicates that if methods could be developed for the isolation of these pathways and production of their target molecules in heterologous hosts, great numbers of potentially valuable compounds might be discovered. In these investigations, large insert libraries of two microorganisms were constructed, one a bacterial artificial chromosome (BAC) library, the other a fosmid library, and two large insert fosmid libraries were constructed with DNA isolated from marine environmental samples. A mathematical formula was derived to estimate probabilities of cloning intact biosynthetic pathways with large insert genomic libraries and tested with a computer simulation. This indicated that even large pathways could be cloned intact in large insert libraries, provided there was an adequate size difference between the target pathway and the library inserts, and there was a concomitant increase in the size of the library with the targeting of these larger pathways. In addition, an investigation into a mixed marine culture sample lead to the identification of an unusual relationship between two bacteria for which extended co-culture leads to the production of pyocyanin. However, no useful biosynthetic pathways were located within the genomic libraries. It is concluded that significant improvements would be required to make this approach feasible for larger scale investigations. It is further concluded, on the basis of recent developments in the field, including a reduction in the cost of sequencing, improvements in techniques of whole-genome shotgun sequencing, and the development of recombination based cloning, that the employment of mass sequencing efforts and sequence-driven, recombinationbased cloning, might prove to be a more fruitful and efficient alternative to large-insert library construction for the isolation and expression of these pathways. A possible paradigm for the cloning of pathways on the basis of this technology is proposed

Prognostic Molecular Markers of Response to Radiotherapy in Rectal Cancer

Colorectal cancer (CRC) is the second most deadly cancer globally, and 30% of these cancers occur in the rectum. The primary treatment for CRC is surgery, often radiotherapy with adjuvant chemotherapy is used before or following surgical resection. Treatment carries with it a high cost and side effect burden while response rates remain unpredictable. Approximately 20% of patients have total tumour regression post chemoradiotherapy; however, most patients receive only partial or no benefit from treatment. The ability to predict which patients would benefit from standard treatment and those who should be directed to an alternative treatment or an accelerated pathway to surgery would potentially avoid lengthy and costly treatments that may only cause side effects for patients, improving survival rates and quality of life. In this study, the microbiome, immune cells and patient gene expression were evaluated for their use as predictive biomarkers for response to chemoradiotherapy in rectal cancer patients. Tumour and adjacent normal tissue biopsies were taken before treatment and had DNA and RNA extracted and sequenced. First, the methodology for analysing microbiomes via shotgun sequencing data was evaluated and improved, increasing taxonomic assignment accuracy by 11% and potentially decreasing analysis time more than nine-fold. Secondly, the sequencing technologies, Oxford Nanopore, 16S rRNA and RNA-sequencing, were evaluated for their ability to assess the microbiome. The results demonstrated that platforms had concordance with one another; however, this was reduced at the species level. Third, microbial transcription was used to assess rectal cancer microbiomes, correlating them with response rates. The results showed that microbial diversity did not contribute to radiotherapy response, but that individual microbes may influence response. It was hypothesised that species such as Hungatella hathewayi, Fusobacterium nucleatum, Butyricimonas faecalis, Alistipes finegoldii, Bacteroides thetaiotaomicron, and B. fragilis may contribute to tumour regression by modulating metabolism and immune responses. Third, the abundance of infiltrating immune cells was predicted using RNA-Sequencing data. Analysis indicated that the abundance of M1 macrophages and resting mast cells were correlated with response, while microbial transcription was correlated with the abundance of allergic and anti-tumour effector cells, as well as antigen-presenting cells. It was hypothesised that the microbiome might modulate anti-tumour immune responses directly, and indirectly by altering the tumour microenvironment. Microbes may help maintain a population of anti-tumour effector and antigen-presenting cells for tumour-antigen presentation during tumour cell death and neo-antigen uptake, which may be otherwise exhausted by targeting aspects of the inflammatory tumour microenvironment (i.e., lipid phagocytosis, anti-bacterial and allergic responses). Lastly, machine-learning was employed to establish a panel of molecular biomarkers predictive of response, including microbial transcription, immune cells and gene expression. The final model demonstrated the ability to predict response with a 7% overall error rate, and that predicting response relied mostly on normal and tumour tissue gene expression, and tumour infiltrating immune cells. This study provides a panel of prognostic biomarkers which could be utilised to predict patient response. Additionally, it provides evidence for microbial-immune interactions that could be manipulated to enhance treatment and increase response rates