Five statistical questions about the tree of life

Stochastic modeling of phylogenies raises five questions that have received varying levels of attention from quantitatively inclined biologists. 1) How large do we expect (from the model) the ratio of maximum historical diversity to current diversity to be? 2) From a correct phylogeny of the extant species of a clade, what can we deduce about past speciation and extinction rates? 3) What proportion of extant species are in fact descendants of still-extant ancestral species, and how does this compare with predictions of models? 4) When one moves from trees on species to trees on sets of species (whether traditional higher order taxa or clades within PhyloCode), does one expect trees to become more unbalanced as a purely logical consequence of tree structure, without signifying any real biological phenomenon? 5) How do we expect that fluctuation rates for counts of higher order taxa should compare with fluctuation rates for number of species? We present a mathematician's view based on an oversimplified modeling framework in which all these questions can be studied coherently.     

Life With or Without Names

The terms ‘life’, ‘species’ and ‘individuals’ are key concepts in biology. However, theoretical and practical concerns are directly associated with definitions of these terms and their use in researchers’ work. Although the practical implications of employing definition of ‘species’ and ‘individuals’ are often clear, it is surprising how most biologists work in their field of study without adhering to a specific definition of life. In everyday scientific practice, biologists rarely define life. This is somewhat understandable: the majority of biologists accept the standard definition of life without exploring it, but this represents a bad attitude. In this essay, we update the concepts of life, species, and individuals in the light of the new techniques for massive DNA sequencing collectively known as high throughput DNA sequencing (HTS). A re-evaluation of the newest approaches and traditional concepts is required, because in many scientific publications, HTS users apply concepts ambiguously (in particular that of species). However, the absence of clarity is understandable. For most of the last 250 years, from Linnaeus to the most recent researches, identification and classification have been performed applying the same process. On the contrary, through HTS, biologists have become simply identifiers, who construct boundaries around the biological entities and do not examine the taxa at length, resulting in uncertainty in most readers and displeasure in traditional taxonomists. We organised our essay to answer a basic question: can we develop new means to observe living organisms?     

An algorithm for targeted convergence of Euler or Newton iterations

The concept of multistationarity has become essential for understanding cell differentiation. For this reason theoretical biologists have more and more frequently to determine the steady values, often multiple, of systems of non-linear differential equations. It is well known that iteration processes of current use converge or not towards a fixed point depending on the absolute value of the slope of the iteration function in the vicinity of the considered fixed point. A number of methods have been developed to obtain or accelerate convergence. As biologists, we do not pretend to review these works. Rather, we propose here a simple algorithm which permits to converge at will towards a chosen type of steady state. Others and we have used this procedure extensively for years for the analysis of complex biological systems. A compact program (using Mathematica) is available.     

Integrating evolutionary and molecular genetics of aging

Aging or senescence is an age-dependent decline in physiological function, demographically manifest as decreased survival and fecundity with increasing age. Since aging is disadvantageous it should not evolve by natural selection. So why do organisms age and die? In the 1940s and 1950s evolutionary geneticists resolved this paradox by positing that aging evolves because selection is inefficient at maintaining function late in life. By the 1980s and 1990s this evolutionary theory of aging had received firm empirical support, but little was known about the mechanisms of aging. Around the same time biologists began to apply the tools of molecular genetics to aging and successfully identified mutations that affect longevity. Today, the molecular genetics of aging is a burgeoning field, but progress in evolutionary genetics of aging has largely stalled. Here we argue that some of the most exciting and unresolved questions about aging require an integration of molecular and evolutionary approaches. Is aging a universal process? Why do species age at different rates? Are the mechanisms of aging conserved or lineage-specific? Are longevity genes identified in the laboratory under selection in natural populations? What is the genetic basis of plasticity in aging in response to environmental cues and is this plasticity adaptive? What are the mechanisms underlying trade-offs between early fitness traits and life span? To answer these questions evolutionary biologists must adopt the tools of molecular biology, while molecular biologists must put their experiments into an evolutionary framework. The time is ripe for a synthesis of molecular biogerontology and the evolutionary biology of aging.     

Controlling morpholino experiments: don't stop making antisense

One of the most significant problems facing developmental biologists who do not work on an organism with well-developed genetics - and even for some who do - is how to inhibit the action of a gene of interest during development so as to learn about its normal biological function. A widely adopted approach is to use antisense technologies, and especially morpholino antisense oligonucleotides. In this article, we review the use of such reagents and present examples of how they have provided insights into developmental mechanisms. We also discuss how the use of morpholinos can lead to misleading results, including off-target effects, and we suggest controls that will allow researchers to interpret morpholino experiments correctly.     

Parts plus pipes: synthetic biology approaches to metabolic engineering

Synthetic biologists combine modular biological "parts" to create higher-order devices. Metabolic engineers construct biological "pipes" by optimizing the microbial conversion of basic substrates to desired compounds. Many scientists work at the intersection of these two philosophies, employing synthetic devices to enhance metabolic engineering efforts. These integrated approaches promise to do more than simply improve product yields; they can expand the array of products that are tractable to produce biologically. In this review, we explore the application of synthetic biology techniques to next-generation metabolic engineering challenges, as well as the emerging engineering principles for biological design.     

Getting the most from PSI-BLAST

Most biologists now conduct sequence searches as a matter of course. But how do we know that a relationship predicted by a homology search is a true, rather than false, hit with the same score? Many biologists design their own experiments with exquisite care yet still assume that results from programs with more than 20 adjustable parameters are 100% reliable. This article explains some of the key steps in getting the most from PSI-Blast, one of the most popular and powerful homology search programs currently available.     

Biodiversity,biological uncertainty,and setting conservation priorities

In a world of massive extinctions where not all taxa can be saved, how ought biologists to decide their preservation priorities? When biologists make recommendations regarding conservation, should their analyses be based on scientific criteria, on public or lay criteria, on economic or some other criteria? As a first step in answering this question, we examine the issue of whether biologists ought to try to save the endangered Florida panther, a well known “glamour” taxon. To evaluate the merits of panther preservation, we examine three important arguments of biologists who are skeptical about the desirability of panther preservation. These arguments are (1) that conservation dollars ought to be spent in more efficient ways than panther preservation; (2) that biologists and conservationists ought to work to preserve species before subspecies; and (3) that biologists and conservationists ought to work to save habitats before species or subspecies. We conclude that, although all three arguments are persuasive, none of them provides convincing grounds for foregoing panther preservation in favor of other, more scientifically significant conservation efforts. Our conclusion is based, in part, on the argument that biologists ought to employ ethical, as well as scientific, rationality in setting conservation priorities and that ethical rationality may provide persuasive grounds for preserving taxa that often are not viewed by biologists as of great importance.     

物种形成基因及其功能

什么是物种?新物种是如何形成的？这些问题是生命科学研究的重大问题.物种的形成是在生殖隔离的基础上某些新的生物学性状的形成和保留,是生物进化的最基本过程,其实质是基因结构突变的积累与功能的分化. 地理隔离使群体中的基因不能交流,基因突变也会影响个体间交配趣向,从而造成交配隔离或者交配后杂合体的基因组不亲和、杂交不育甚至杂交不活,使不同的群体逐渐分化为新物种. 随着分子生物学与基因组学的飞速发展,进化生物学家已经发现一些与物种形成有关的基因-物种形成基因（speciation genes）,鉴定并了解这些基因的功能,不仅能使我们在分子水平上理解新物种形成的实质和规律、而且对于我们突破种间屏障进行远缘杂交育种也有重要的理论指导意义.本文综述了目前对几个物种形成基因及其功能的研究进展,为该领域的进一步研究提供资料.     

Setup of a scientific computing environment for computational biology: Simulation of a genome-scale metabolic model of Escherichia coli as an example

Computational analysis of biological data is becoming increasingly important, especially in this era of big data. Computational analysis of biological data allows efficiently deriving biological insights for given data, and sometimes even counterintuitive ones that may challenge the existing knowledge. Among experimental researchers without any prior exposure to computer programming, computational analysis of biological data has often been considered to be a task reserved for computational biologists. However, thanks to the increasing availability of user-friendly computational resources, experimental researchers can now easily access computational resources, including a scientific computing environment and packages necessary for data analysis. In this regard, we here describe the process of accessing Jupyter Notebook, the most popular Python coding environment, to conduct computational biology. Python is currently a mainstream programming language for biology and biotechnology. In particular, Anaconda and Google Colaboratory are introduced as two representative options to easily launch Jupyter Notebook. Finally, a Python package COBRApy is demonstrated as an example to simulate 1) specific growth rate of Escherichia coli as well as compounds consumed or generated under a minimal medium with glucose as a sole carbon source, and 2) theoretical production yield of succinic acid, an industrially important chemical, using E. coli. This protocol should serve as a guide for further extended computational analyses of biological data for experimental researchers without computational background.     

The Living State

As biologists we can contribute to quantum chemistry only by clearing up the mechanism of some of the biological processes, thereby opening the way to their quantum chemical analysis. We have tried to do this by isolating and identifying the central catalysts of those processes. One of us (A.S.-G.) studied biological oxidations first in the plants that turn dark on exposure to air such as potatoes, apples and pears. He found the central catalyst of these oxidations to be a catechol derivative that oxidized to o-diquinol which forms dark complexes with protein. After this, he turned to the oxidation of plants that do not turn dark and identified two catalysts, one of which was ascorbic acid, the other succinic acid. His third problem was the generation of motion, the function of muscle. This study led to the discovery of a new protein, which he discovered with I. Banga at the University of Szeged, Hungary. They called it “actin” because it made the inactive myosin act to contract. This discovery has an unusual history. It was never published because just when they were about to publish, Hitler occupied Hungary and Szent-Gyorgyi had to disappear “underground” separated from Banga and science. Our present interest is in the “Living State”, one of the most important phenomena, the central substance of which seems to be methoxyhydroquinone (1–6).     

Potentials and pitfalls of fluorescent quantum dots for biological imaging

Fluorescent semiconductor nanocrystals, known as quantum dots (QDs), have several unique optical and chemical features. These features make them desirable fluorescent tags for cell and developmental biological applications that require long-term, multi-target and highly sensitive imaging. The improved synthesis of water-stable QDs, the development of approaches to label cells efficiently with QDs, and improvements in conjugating QDs to specific biomolecules have triggered the recent explosion in their use in biological imaging. Although there have been many successes in using QDs for biological applications, limitations remain that must be overcome before these powerful tools can be used routinely by biologists.     

Demystifying computer science for molecular ecologists

In this age of data‐driven science and high‐throughput biology, computational thinking is becoming an increasingly important skill for tackling both new and long‐standing biological questions. However, despite its obvious importance and conspicuous integration into many areas of biology, computer science is still viewed as an obscure field that has, thus far, permeated into only a few of the biology curricula across the nation. A national survey has shown that lack of computational literacy in environmental sciences is the norm rather than the exception [Valle & Berdanier (2012) Bulletin of the Ecological Society of America, 93, 373–389]. In this article, we seek to introduce a few important concepts in computer science with the aim of providing a context‐specific introduction aimed at research biologists. Our goal was to help biologists understand some of the most important mainstream computational concepts to better appreciate bioinformatics methods and trade‐offs that are not obvious to the uninitiated.     

Mapping protein post-translational modifications with mass spectrometry

Post-translational modifications of proteins control many biological processes, and examining their diversity is critical for understanding mechanisms of cell regulation. Mass spectrometry is a fundamental tool for detecting and mapping covalent modifications and quantifying their changes. Modern approaches have made large-scale experiments possible, screening complex mixtures of proteins for alterations in chemical modifications. By profiling protein chemistries, biologists can gain deeper insight into biological control. The aim of this review is introduce biologists to current strategies in mass spectrometry-based proteomics that are used to characterize protein post-translational modifications, noting strengths and shortcomings of various approaches.     

Australia's marine biogeography revisited: Back to the future?

The recognition of broad biogeographic provinces provides an important framework for ecological and conservation biological research. Marine biologists have long recognized distinct biogeographic provinces in southern Australia, primarily on the basis of qualitative differences in intertidal species assemblages. Here we provide an a priori test for these traditional eastern (Peronian), western (Flindersian) and south‐eastern (Maugean) provinces. Specifically, we analyse distributional data for approximately 1500 algal species using the newly available Australian Virtual Herbarium, an online database of herbarium specimens. Our quantitative algal analyses across southern Australia identify three distinct biogeographic assemblages, consistent with traditional qualitative provinces. We argue that these broad provinces provide a highly effective framework for understanding and managing Australia's marine biodiversity. In particular, biogeographic provinces provide a regional framework for integrating the ongoing discovery of biological variation at finer scales. More broadly therefore we recommend that biologists undertake quantitative analyses to test provincial biogeographic boundaries around the globe.     

Understanding the Emergence of Cellular Organization

More than one researcher is currently proposing that the notion of information become an important element for defining living systems as well as for explaining conditions that make their origins possible. During the pre-biotic era, the type of compounds encountered would mainly have been very simple in nature and might have been immersed in the natural dynamic of the physical world and in processes of self-organization. It is furthermore quite possible that they formed a relationship between and among certain types of processes that here we are specifically proposing as central for the emergence of cell organization. Consequently, an important initial step towards constructing a theory of biological information is to ask ourselves the question: how do biological systems process information? In this way, we will be contributing to the proposals of this paper where we seek to identify general principles that govern biological computing and that deal with biosemiotic approaches as they are defended in naturalistic normative terms.     

What makes an endurance athlete world-class? Not simply a physiological conundrum

Inter-individual variation in endurance performance capacity is a characteristic, not only of the general population, but also in trained athletes. The ability of sport scientists to predict which athletes amongst an elite group will become world-class is limited. We do not fully understand the interactions between biological factors, training, recovery and competitive performance. Assessment methods and interpretation of results do not take into account the facts that most research is not done on elite athletes and performances of world-class endurance athletes cannot be attributed to aerobic capacity alone. Many lines of evidence suggest that there is a limit to adaptation in aerobic capacity. Recent advances in molecular biology and genetics should be harnessed by exercise biologists in conjunction with previously used physiological, histological and biochemical techniques to study elite athletes and their responses to different training and recovery regimens. Technological advances should be harnessed to study world-class athletes to determine optimal training and competition strategies. In summary, it is likely that multiple factors are essential contributors to world-class endurance performance and that it is only by using a multidisciplinary approach that we will come closer to solving the conundrum: 'What makes an endurance athlete world class?'     

Automated protein function prediction--the genomic challenge

Overwhelmed with genomic data, biologists are facing the first big post-genomic question--what do all genes do? First, not only is the volume of pure sequence and structure data growing, but its diversity is growing as well, leading to a disproportionate growth in the number of uncharacterized gene products. Consequently, established methods of gene and protein annotation, such as homology-based transfer, are annotating less data and in many cases are amplifying existing erroneous annotation. Second, there is a need for a functional annotation which is standardized and machine readable so that function prediction programs could be incorporated into larger workflows. This is problematic due to the subjective and contextual definition of protein function. Third, there is a need to assess the quality of function predictors. Again, the subjectivity of the term 'function' and the various aspects of biological function make this a challenging effort. This article briefly outlines the history of automated protein function prediction and surveys the latest innovations in all three topics.     

What,if anything,is sympatric speciation?

Sympatric speciation has always fascinated evolutionary biologists, and for good reason; it pits diversifying selection directly against the tendency of sexual reproduction to homogenize populations. However, different investigators have used different definitions of sympatric speciation and different criteria for diagnosing cases of sympatric speciation. Here, we explore some of the definitions that have been used in empirical and theoretical studies. Definitions based on biogeography do not always produce the same conclusions as definitions based on population genetics. The most precise definitions make sympatric speciation an infinitesimal end point of a continuum. Because it is virtually impossible to demonstrate the occurrence of such a theoretical extreme, we argue that testing whether a case fits a particular definition is less informative than evaluating the biological processes affecting divergence. We do not deny the importance of geographical context for understanding divergence. Rather, we believe this context can be better understood by modelling and measuring quantities, such as gene flow and selection, rather than assigning cases to discrete categories like sympatric and allopatric speciation.