Gut Colonization Mechanisms of Lactobacillus and Bifidobacterium: An Argument for Personalized Designs

2020 ◽  
Vol 12 (1) ◽  
Author(s):  
Yue Xiao ◽  
Qixiao Zhai ◽  
Hao Zhang ◽  
Wei Chen ◽  
Colin Hill
Keyword(s):  
Machine Learning ◽  
Natural History ◽  
Molecular Mechanisms ◽  
Annual Review ◽  
Food Science ◽  
Publication Date ◽  
Host Genotype ◽  
Gut Colonization ◽  
Colonization Process ◽  
Metabolic Interactions

Lactobacillus and Bifidobacterium spp. are best understood for their applications as probiotics, which are often transient, but as commensals it is probable that stable colonization in the gut is important for their beneficial roles. Recent research suggests that the establishment and persistence of strains of Lactobacillus and Bifidobacterium in the gut are species- and strain-specific and affected by natural history, genomic adaptability, and metabolic interactions of the bacteria and the microbiome and immune aspects of the host but also regulated by diet. This provides new perspectives on the underlying molecular mechanisms. With an emphasis on host–microbe interaction, this review outlines how the characteristics of individual Lactobacillus and Bifidobacterium bacteria, the host genotype and microbiome structure, diet, and host–microbe coadaptation during bacterial gut transition determine and influence the colonization process. The diet-tuned and personally tailored colonization can be achieved via a machine learning prediction model proposed here. Expected final online publication date for the Annual Review of Food Science and Technology, Volume 12 is March 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Origin and Early Evolution of the Eukaryotic Cell

2021 ◽  
Vol 75 (1) ◽  
Author(s):  
Toni Gabaldón
Keyword(s):  
Current Knowledge ◽  
Eukaryotic Cell ◽  
Early Evolution ◽  
Annual Review ◽  
Publication Date ◽  
Eukaryotic Evolution ◽  
Life Itself ◽  
Metabolic Interactions ◽  
Phylogenomic Analyses ◽  
Origin Of Eukaryotes

The origin of eukaryotes has been defined as the major evolutionary transition since the origin of life itself. Most hallmark traits of eukaryotes, such as their intricate intracellular organization, can be traced back to a putative common ancestor that predated the broad diversity of extant eukaryotes. However, little is known about the nature and relative order of events that occurred in the path from preexisting prokaryotes to this already sophisticated ancestor. The origin of mitochondria from the endosymbiosis of an alphaproteobacterium is one of the few robustly established events to which most hypotheses on the origin of eukaryotes are anchored, but the debate is still open regarding the time of this acquisition, the nature of the host, and the ecological and metabolic interactions between the symbiotic partners. After the acquisition of mitochondria, eukaryotes underwent a fast radiation into several major clades whose phylogenetic relationships have been largely elusive. Recent progress in the comparative analyses of a growing number of genomes is shedding light on the early events of eukaryotic evolution as well as on the root and branching patterns of the tree of eukaryotes. Here I discuss current knowledge and debates on the origin and early evolution of eukaryotes. I focus particularly on how phylogenomic analyses have challenged some of the early assumptions about eukaryotic evolution, including the widespread idea that mitochondrial symbiosis in an archaeal host was the earliest event in eukaryogenesis. Expected final online publication date for the Annual Review of Microbiology, Volume 75 is October 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

scholarly journals Modern Clinical Text Mining: A Guide and Review

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Bethany Percha
Keyword(s):  
Machine Learning ◽  
Text Mining ◽  
Data Science ◽  
Annual Review ◽  
Publication Date ◽  
Biomedical Data ◽  
Clinical Text ◽  
Quality Improvement Research ◽  
Comprehensive Survey ◽  
Technical Advances

Electronic health records (EHRs) are becoming a vital source of data for healthcare quality improvement, research, and operations. However, much of the most valuable information contained in EHRs remains buried in unstructured text. The field of clinical text mining has advanced rapidly in recent years, transitioning from rule-based approaches to machine learning and, more recently, deep learning. With new methods come new challenges, however, especially for those new to the field. This review provides an overview of clinical text mining for those who are encountering it for the first time (e.g., physician researchers, operational analytics teams, machine learning scientists from other domains). While not a comprehensive survey, this review describes the state of the art, with a particular focus on new tasks and methods developed over the past few years. It also identifies key barriers between these remarkable technical advances and the practical realities of implementation in health systems and in industry. Expected final online publication date for the Annual Review of Biomedical Data Science, Volume 4 is July 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Molecular Force Measurement with Tension Sensors

2021 ◽  
Vol 50 (1) ◽  
Author(s):  
Lisa S. Fischer ◽  
Srishti Rangarajan ◽  
Tanmay Sadhanasatish ◽  
Carsten Grashoff
Keyword(s):  
Molecular Mechanisms ◽  
Force Measurement ◽  
Annual Review ◽  
Publication Date ◽  
Mechanical Forces ◽  
Biophysical Parameters ◽  
Cellular Mechanotransduction ◽  
Molecular Force ◽  
Molecular Forces ◽  
Physical Principles

The ability of cells to generate mechanical forces, but also to sense, adapt to, and respond to mechanical signals, is crucial for many developmental, postnatal homeostatic, and pathophysiological processes. However, the molecular mechanisms underlying cellular mechanotransduction have remained elusive for many decades, as techniques to visualize and quantify molecular forces across individual proteins in cells were missing. The development of genetically encoded molecular tension sensors now allows the quantification of piconewton-scale forces that act upon distinct molecules in living cells and even whole organisms. In this review, we discuss the physical principles, advantages, and limitations of this increasingly popular method. By highlighting current examples from the literature, we demonstrate how molecular tension sensors can be utilized to obtain access to previously unappreciated biophysical parameters that define the propagation of mechanical forces on molecular scales. We discuss how the methodology can be further developed and provide a perspective on how the technique could be applied to uncover entirely novel aspects of mechanobiology in the future. Expected final online publication date for the Annual Review of Biophysics, Volume 50 is May 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Plant-Based Proteins: The Good, Bad, and Ugly

2022 ◽  
Vol 13 (1) ◽  
Author(s):  
William R. Aimutis
Keyword(s):  
Agricultural Production ◽  
Future Generations ◽  
Annual Review ◽  
Food Science ◽  
Publication Date ◽  
The Past ◽  
Per Capita ◽  
Consumption Enjoyment ◽  
Global Population ◽  
Made In

Our global population is growing at a pace to exceed 10 billion people by the year 2050. This growth will place pressure on the agricultural production of food to feed the hungry masses. One category that will be strained is protein. Per capita protein consumption is rising in virtually every country for both nutritional reasons and consumption enjoyment. The United Nations estimates protein demand will double by 2050, and this will result in a critical overall protein shortage if drastic changes are not made in the years preceding these changes. Therefore, the world is in the midst of identifying technological breakthroughs to make protein more readily available and sustainable for future generations. One protein sourcing category that has grown in the past decade is plant-based proteins, which seem to fit criteria established by discerning consumers, including healthy, sustainable, ethical, and relatively inexpensive. Although demand for plant-based protein continues to increase, these proteins are challenging to utilize in novel food formulations. Expected final online publication date for the Annual Review of Food Science and Technology, Volume 13 is March 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Molecular Origins of Polymorphism in Cocoa Butter

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Saeed M. Ghazani ◽  
Alejandro G. Marangoni
Keyword(s):  
Cocoa Butter ◽  
Ternary Phase ◽  
Annual Review ◽  
Food Science ◽  
Publication Date ◽  
Polymorphic Transformations ◽  
Crystal Forms ◽  
Polymorphic Forms ◽  
Phase Behaviors ◽  
Metastable Forms

Cocoa butter displays complex crystallization behavior and six crystal polymorphic forms. Although the crystal structure of cocoa butter has been studied extensively, the molecular interactions between cocoa butter triacylglycerols in relation to polymorphic transformations from metastable forms (forms III and IV) to stable crystal forms (forms V and VI) remain largely unknown. In this review, the triclinic polymorphism and melting profiles of the major triacylglycerols in cocoa butter—POP, POS, and SOS—are reviewed, and their binary and ternary phase behaviors in metastable (pseudoβ′) and stable (β2) crystal forms are discussed. We also attempt to clarify how the transformation of cocoa butter from form IV to V, as a critical step in the tempering of chocolate, is controlled by POS interactions with both POP and SOS. Moreover, we show how the crystal forms V and VI of cocoa butter are templated by crystal forms β3 and β1 of POS, respectively. Expected final online publication date for the Annual Review of Food Science and Technology, Volume 12 is March 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Systems Biology of the Vasopressin V2 Receptor: New Tools for Discovery of Molecular Actions of a GPCR

2021 ◽  
Vol 62 (1) ◽  
Author(s):  
Lihe Chen ◽  
Hyun Jun Jung ◽  
Arnab Datta ◽  
Euijung Park ◽  
Brian G. Poll ◽  
...  
Keyword(s):  
Systems Biology ◽  
Large Scale ◽  
Molecular Mechanisms ◽  
Water Channel ◽  
Peptide Hormone ◽  
Annual Review ◽  
Publication Date ◽  
Large Scale Data ◽  
V2 Receptor ◽  
Scale Data

Systems biology can be defined as the study of a biological process in which all of the relevant components are investigated together in parallel to discover the mechanism. Although the approach is not new, it has come to the forefront as a result of genome sequencing projects completed in the first few years of the current century. It has elements of large-scale data acquisition (chiefly next-generation sequencing–based methods and protein mass spectrometry) and large-scale data analysis (big data integration and Bayesian modeling). Here we discuss these methodologies and show how they can be applied to understand the downstream effects of GPCR signaling, specifically looking at how the neurohypophyseal peptide hormone vasopressin, working through the V2 receptor and PKA activation, regulates the water channel aquaporin-2. The emerging picture provides a detailed framework for understanding the molecular mechanisms involved in water balance disorders, pointing the way to improved treatment of both polyuric disorders and water-retention disorders causing dilutional hyponatremia. Expected final online publication date for the Annual Review of Pharmacology and Toxicology, Volume 62 is January 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Molecules from the Microbiome

2021 ◽  
Vol 90 (1) ◽  
Author(s):  
Emilee E. Shine ◽  
Jason M. Crawford
Keyword(s):  
Small Molecules ◽  
Molecular Mechanisms ◽  
System Development ◽  
Human Microbiome ◽  
Host Responses ◽  
Annual Review ◽  
Publication Date ◽  
Mechanistic Studies ◽  
Immune System Development ◽  
Interdisciplinary Approaches

The human microbiome encodes a second genome that dwarfs the genetic capacity of the host. Microbiota-derived small molecules can directly target human cells and their receptors or indirectly modulate host responses through functional interactions with other microbes in their ecological niche. Their biochemical complexity has profound implications for nutrition, immune system development, disease progression, and drug metabolism, as well as the variation in these processes that exists between individuals. While the species composition of the human microbiome has been deeply explored, detailed mechanistic studies linking specific microbial molecules to host phenotypes are still nascent. In this review, we discuss challenges in decoding these interaction networks, which require interdisciplinary approaches that combine chemical biology, microbiology, immunology, genetics, analytical chemistry, bioinformatics, and synthetic biology. We highlight important classes of microbiota-derived small molecules and notable examples. An understanding of these molecular mechanisms is central to realizing the potential of precision microbiome editing in health, disease, and therapeutic responses. Expected final online publication date for the Annual Review of Biochemistry, Volume 90 is June 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

The Influence of the Western Diet on Microbiota and Gastrointestinal Immunity

2022 ◽  
Vol 13 (1) ◽  
Author(s):  
Vanessa Las Heras ◽  
Silvia Melgar ◽  
John MacSharry ◽  
Cormac G.M. Gahan
Keyword(s):  
Immune Function ◽  
Western Diet ◽  
Major Influence ◽  
Annual Review ◽  
Food Science ◽  
Publication Date ◽  
Gastrointestinal Microbiota ◽  
Human Diet ◽  
Regulatory Processes ◽  
Inflammatory Bowel

Diet exerts a major influence upon host immune function and the gastrointestinal microbiota. Although components of the human diet (including carbohydrates, fats, and proteins) are essential sources of nutrition for the host, they also influence immune function directly through interaction with innate and cell-mediated immune regulatory mechanisms. Regulation of the microbiota community structure also provides a mechanism by which food components influence host immune regulatory processes. Here, we consider the complex interplay between components of the modern (Western) diet, the microbiota, and host immunity in the context of obesity and metabolic disease, inflammatory bowel disease, and infection. Expected final online publication date for the Annual Review of Food Science and Technology, Volume 13 is March 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

scholarly journals Neural Network Potentials: A Concise Overview of Methods

2022 ◽  
Vol 73 (1) ◽  
Author(s):  
Emir Kocer ◽  
Tsz Wai Ko ◽  
Jörg Behler
Keyword(s):  
Machine Learning ◽  
Atomic Structure ◽  
Electrostatic Interactions ◽  
Large Scale ◽  
Machine Learning Algorithms ◽  
Annual Review ◽  
Publication Date ◽  
Great Success ◽  
Concise Overview ◽  
Wide Range

In the past two decades, machine learning potentials (MLPs) have reached a level of maturity that now enables applications to large-scale atomistic simulations of a wide range of systems in chemistry, physics, and materials science. Different machine learning algorithms have been used with great success in the construction of these MLPs. In this review, we discuss an important group of MLPs relying on artificial neural networks to establish a mapping from the atomic structure to the potential energy. In spite of this common feature, there are important conceptual differences among MLPs, which concern the dimensionality of the systems, the inclusion of long-range electrostatic interactions, global phenomena like nonlocal charge transfer, and the type of descriptor used to represent the atomic structure, which can be either predefined or learnable. A concise overview is given along with a discussion of the open challenges in the field. Expected final online publication date for the Annual Review of Physical Chemistry, Volume 73 is April 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

scholarly journals Algorithmic Fairness: Choices, Assumptions, and Definitions

2020 ◽  
Vol 8 (1) ◽  
Author(s):  
Shira Mitchell ◽  
Eric Potash ◽  
Solon Barocas ◽  
Alexander D’Amour ◽  
Kristian Lum
Keyword(s):  
Machine Learning ◽  
Decision Making ◽  
Rapid Growth ◽  
Online Publication ◽  
Annual Review ◽  
Publication Date ◽  
Learning Models ◽  
Fairness Concerns ◽  
Machine Learning Models

A recent wave of research has attempted to define fairness quantitatively. In particular, this work has explored what fairness might mean in the context of decisions based on the predictions of statistical and machine learning models. The rapid growth of this new field has led to wildly inconsistent motivations, terminology, and notation, presenting a serious challenge for cataloging and comparing definitions. This article attempts to bring much-needed order. First, we explicate the various choices and assumptions made—often implicitly—to justify the use of prediction-based decision-making. Next, we show how such choices and assumptions can raise fairness concerns and we present a notationally consistent catalog of fairness definitions from the literature. In doing so, we offer a concise reference for thinking through the choices, assumptions, and fairness considerations of prediction-based decision-making. Expected final online publication date for the Annual Review of Statistics, Volume 8 is March 8, 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

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