Index: Evolution's Clinical Guidebook

In the past few blogs, I've been discussing the recent publication of my book, Evolution’s Clinical Guidebook: Translating Ancient Genes Into Precision Medicine. The premise of this book is that modern medicine is based on an understanding of evolutionary processes. Evolution shows us the relationships between the subdisciplines of medicine that benefit directly from Precision Medicine (i.e., pathology, microbiology, clinical genetics, pharmacology, and bioinformatics). In Evolution's Clinical Guidebook, all of these diverse fields are brought together, under the subject of evolution. To illustrate, I have listed below the first few pages of the index to the book (letters A through H). Just by perusing these index terms, you can get some idea of the role played by evolution as the great unifier of modern medicine.

Partial Book Index

A 
Abiogenesis 
  catalysts, 2 
  cellular life, 
  earliest signs of, 4 
  definition, 1
  DNA, 4 
  evolution, 2 
  life on earth, 1 
  natural selection, 2
  RNA, 4­5
Acanthodians, 215
Acarnus erithacus, 192, 192f 
Acidianus Tailed Virus, 160
Acquired disease, 20, 29-­30
Actin, 17
Actinistia, 216
Actinopterygii, 215
Adaptive immune system, 214
Adaptive immunity, 161, 164
Adenocarcinoma, 125, 126-­127f Adult organisms, 94, 102
Agenesis of the Corpus Callosum (ACC), 222
Aging, 77, 216, 257-­258, 261-­265 
  vs. diseases of old people, 257-­259 
  evolution of, 252­-265 gene, 257­-258
Agnatha, 214
Allele, 77
Allium cepa, 66
Allium ursinum, 66 alphaA-Crystallin, 18
Alstrom syndrome, 213-­214
Alternative RNA splicing, 126
Amanita phalloides, 155
Amborella trichopoda, 150
Ambulacraria, 197
Amniotes, 218
Amoebozoa, 184, 290
Amphibia, 216­218
Amphioxus, 150
Amyloid world, 30
Anatomy, 246
Ancestral classes, 175-­176, 196­-197
Ancestral lineage, 12
Ancestral species, 12
  eukaryotic development, steps in, 14-­15, 15f 
  gene families, 13­-14
Ancylostoma duodenale, 292
Androgenesis, 221
Aneuploidy, 69­70, 70f Angelman syndrome, 222
Angiogenesis, 126
Angiosperma, 29­-44
Animal cells, 262
Animalia, 27f 
Animal model, human disease 
  Koch's postulates and reliance, 299-­300 
  nonhuman eutherians, 285 
  non-vertebrate models, cancer research, 298-­299 
  for orthodiseases
    Caenorhabditis elegans (nematodes), 294, 296-­298, 297f
    Danio rerio (zebrafish), 294, 297-­298, 298f 
    Drosophila melanogaster (fruit fly), 294, 297 
  homologous genes, 296 
  human pathologic processes, 295 
  orthologous genes, 295­-296
  Saccharomyces cerevisiae (yeast), 294­-296, 296f 
  rabbits, myxoma virus on, 300-­302 
  rats, 285 
  specificities and idiosyncrasies
    clinical trial, 286­-287
    Gram-negative organisms, 286 
    infections, history of, 290­-291, 293-­294 
    inflammatory response, 287 
    lipopolysaccharide, 286 
    mice, 286­288 
    microorganisms, potential pathogens, 288-­290 
    rodent models, 287-­288
  TGN1412, 286­287
Anlagen, 127
Aplastic anemia, 270
Apoikozoa, 186­-187
Apomorphy, 198
Apoptosis, 53
Archaea, 26, 27f 
Archaeplastida, 14-­15, 28, 186
Archiplastidae, 185
Arrhythmogenic cardiomyopathies, 191
Arthropods, hepatopancreas of, 118-­119
Ascaris lumbricoides, 292
Aspergillus flavus, 155
Association vs. cause, 77
Ataxia telangiectasia, 30
Atlantogenata, 229
Autism, 58
Autoantibody disease vs. autoimmune disease, 233
Autosomal dominance, 270
Azacytidine, 122

B 
Bacillus globigii, 288
Bacillus subtilis, 244
Bacteria, 26
Baraitser-Winter syndrome, 57
Bartonella species, 26
Basal cell carcinomas, 223-­224, 223f Basal layer, 255
Benign tumor, 218, 233
Bikonta, 183­184
Bilateria, 94, 193­203, 254
Bioinformatics, 78
Biological diversity, 152
Biological theory, 308
Biopsy specimen, 255f Biosphere, 157
Biosynthetic cycle, 17
BK polyomavirus, 292
Blastocystis hominis, 289
Blastula, 191
Blastulation, 189, 190f Blended class, 322, 325
Blood, photomicrograph of, 108f Bloom syndrome, 262
Bone marrow, 256
Bookie, 266
Bootstrapping paradoxes, 5
  chicken and egg paradox, 6­8 
  enzyme and enzyme-synthesizing machinery, 8 
  general solution for, 11-­12 
  hardware or software, 5­6 
  process of evolution and product of evolution, 9-­10
  RNA and DNA, 8­9, 10f 
  species and class of animals, 10-­11
Borderland of Embryology and Pathology, 118-­120
Boreoeutheria, 229
Borhing-Opitz syndrome, 57
Brassica oleracea, 158
BRCA, 271
BRCA1 gene, 269
BRCA2 gene, 269
Breast cancer, 260
Breeds, 248, 249f Brugia malayi, 292
Bryophyte life cycle, 7
Bryophytes, 7
BUB1B gene, 70
Bubonic plague, 292
Bungarus caeruleus, 110f "But-for" test, 30

C 
Caenorhabditis elegans, 65, 123, 294, 296-­298, 297f Calvin cycle, 17
Cambrian explosion, 21­-25, 21­-22f, 155-­156, 185 
  coexistence and coevolution, 25­26
  animals (class Metazoa), 28
  Archaea, 26, 27f 
  Archaeplastida (plants), 28 
  bacteria, 26 
  fungi, 28 
  single-celled eukaryotes, 28 
  viruses, 26
Cambrian period, 21-­22, 22f, 24
Cancer, 259­261
Cancer cells, 51
Cancer progression, 30
Carcinogen, 127
Carcinogenesis, 17, 30-­31, 223
Carcinoid tumors, 211
Carcinosarcomas, of uterus, 119
Caretaker diploid organism, 7
Carotenoids, 156
Carrier, 26, 31 asymptomatic, 27
Catarrhini, 231
Cause, 19, 24, 28
Cell types, epigenome and evolution of, 103-­115
Cell-type-specific gene expression, 112
Cenancestor, 37
Cephalochordata, 198­-203
Cercopithecoidea, 231
Chagas disease, 28, 269-­270
Chance occurrence, 9­10, 31
Channelopathy, 127
Charcot-Marie-Tooth disease, 261
CHARGE syndrome, 57
Chemical diversity, 154
Chemokine, 293, 301
Child class, 198
Chimeric Antigen Receptor for T cells (CAR-T) therapy, 157, 164
Chitin, 185
Chlamydia trachomatis, 292
Chloroplast evolution, 14­15, 17, 31
Choanoflagellatea, 186­187
Choanozoa. See Apoikozoa Chondrichthyes, 215
Chordata, 197­203
Chordoma, 198
Choriocarcinoma, 221
Chromatin, 156
Chromosomal disorder, 271
Chromosomes, 61
  number, variations in, 66
Chronic obstructive pulmonary disease (COPD), 271
Chytrids, 186
Cichlids, 153­154, 154f Ciliopathies, 213-­214, 233
Cis-acting vs. trans-acting, 127-­128
CISD2 gene, 264
Cisd2-null mice, 264
Clade, 128
Cladistics, 198
Class, 7, 32
  of animals, 10, 12, 24­-25 
  of cells, 6 
  of metazoan organisms, 25 
  of organisms, 4­5 
  of paradoxes, 5
Classification, 11 
  data retrieval, 176 vs. diagnosis, 199 
  flying animals, 175 
  formal definition of, 175 
  inferencing, 176 
  mammals, Aristotle, 173-­174 vs. ontology, 177, 198 
  pseudo-scientific assertion, 177 
  self-correction, 177 
  simplification, 175 swimming animals, 175 walking animals, 175
Classification system vs. identification system, 325
Class noise, 322. See also Blended class Clinical trial, 286-­287, 301
Clostridium feseri (blue bacteria), 107f 
Clustered Regularly Interspaced Short
  Palindromic Repeats (CRISPR), 251
Cnidaria, 193
Cnidarian organisms, 193, 195f Coccidia, 28
Cockayne syndrome, 262
Codon, 8, 32
Cofactor, 156, 165
Collision tumor theory, 120
Colon cancers, 119
Combined deficiency, 128
Commensal, 32­33
Competence of classification, 176
Complex disease, 33
Composition theory, 120
Congenital anomaly, 271
Congenital chondrodystrophy, 17-­18
Congenital disorder, 17-­18, 33
Congenital hemangiomas, 119
Connective tissue, 128
Contig disease, 271
Contiguous gene deletion syndrome, 271
Convergence, 165
Conversion theory, 120
Copy number, 78
Corbels, 239-­240
Cornelia de Lange syndrome, 112
Corpus callosum, 222
Cousin class, 167
CpG island, 128
CpG sites, 103
Cranial neural crest, 208
Craniata, 128, 148-­149, 198­-203, 207-­212
Craniates. See Craniata Crocodilia, 218
Crohn's disease, 273
Ctenophora, 193
Ctenophorans, 193, 194f Cyanobacteria, 14­15, 15f, 17, 23, 33
Cyclic neutropenia, 55
Cyclostomata, 211-­212
Cynodonts, 219
Cystic fibrosis transmembrane conductance regulator (CFTR), 113
Cytokine storm, 286-­287
Cytopenia, 78
Cytotrophoblasts, 229


D 
Danio rerio (zebrafish), 294, 297­-298, 298f Daphnia pulex, 154
Darwin's theory, 153
Decitabine, 122 delta1-Crystallin, 18
Demodex, 291
Demospongiae, 192
De novo disease mutations, 56-­58
De novo genes, 74­-76
De novo mutation, 78
Dense core granules, 210
Dermal bones, 209
Dermis, 255
Dermoptera, 230
Desmosomes, 187, 188f, 189, 190f, 191
Deuterostomia, 197
Deuterotomia, 148-­149
Developmental disorder, 128
Devolution, 241
Diagnosis vs. classification, 199
Diamond Blackfan anemia, 210
Diethystilbestrol (DES), 117
Differentiation, 78
Digenic disease, 128­-129
DiGeorge syndrome, 82
Dinosauria, 218
Diploid organism, 7
Dipnomorpha, 216
Dipnotetrapodomorpha, 216
Dipoblasts, 193
Direct mutagen, 52
Direct transdifferentiation, 111
DNA, 73­87
DNA-DNA reassociation kinetics, 151-­152
DNA methylation, 4, 33
DNA repair, 17, 33
Dollo's law, 271
Dormancy, 33
Down syndrome, 56
Driver pathway, 19, 34
Drosophila melanogaster, 101, 294, 297
Drug development, economics of, 20
Druggable driver, 34
Dysgerminomas in women, 102
Dyskeratosis congenita, 262
Dysplasia, 199


E 
Echidnas, 226
Echinodermata, 197
Ectoderm, 129
Eikenella corrodens, 289
Embryo, 99­103 vs. fetus, 129
Embryogenesis, 161
Embryology, relationship between evolution and, 93-­103
Embryonic anlagen, 102
Embryonic stem cell, 129
Endoderm, 6, 34
End-stage condition, 272
Enhancer, 78
Enigmatic pacific hagfish, 211-­212, 212f 
Enterocoelomata. See Deuterostomia Epidermis, 255, 256f 
Epigenome, 4, 34, 221
Epigenome disruptors, 121-­122
Epigenomic methylation, variations in, 65
Epimutation, 129-­130
Epipubic bones, 239
Epistasis, 34­35
Epithelial cell, 130
Epitheliozoa, 193
Epithelium, 189, 189f Erasure, 105-­106, 221
ERCC6 gene, 262
ERCC8 gene, 262
Etiology, 79
Euarchonta, 230
Euarchontoglires, 229-­230
Eugenics, 247-­252
Eugnathostomata, 215
Eukaryota, 15, 148­149
  Bikonta, 183-­184 eukaryotes, 179
  Excavata, 183-­184 
  mitochondria, 180 
  nucleus, 179, 182
  Podiata, 183­184 
  prokaryotic life forms, 179 
  single-celled eukaryotes, 179, 180f 
  Syringammina fragilissima, 179 
  undulipodia, 182
  Unikonta, 183-­184
Eukaryotes, 7, 67, 153­-155, 161, 176, 189
Eumetazoa, 191-­193
Euteleostomi, 215
Eutheria, 97-­98, 226-­235
Eutherians, 226-­235
Evo-devo, 130
Evolutionary convergence, 166
Evolutionary frustration, principle of, 248
Evolution, 
  as fantasy bacterial pathogen, 317­-319 
  disease diagnosis by symptoms, 321­-323 
  drug development and testing, 319 
  homologous genes, 316­317 
  science fiction aficionados, 324 
  speciation, 324 
  taxonomic organisms, treatments for, 319-­321 
  theory of intelligent design, 324-­326
Evolution deniers, 307
Evolvability, 153, 165
Exaptation, 35
Excavata, 183­184, 290
Exome sequencing, 79
Extraembryonic cells, 233
Extraembryonic tissues, 221, 233


F 
Facultative intracellular organism, 79
Fanconi anemia bone marrow failure, 257, 263
Female Anopheles mosquito, 107
Fetal period, 101
Filarial nematodes, 292
Filozoa, 186
First Law of Bioinformatics, 59
Fish, 118-­119
Forme fruste, 130
Founder effect, 13, 35
FOXL2 gene, 112
Fungi, 28, 186, 189


G 
Gallertoids, 130, 187, 191­192
Gametes, 6, 35, 148­-149
Gametic organism, 7
Gametophytes, 7
Gastrointestinal stromal tumors (GISTs), 19
Gastropods, 118-­119
Gene(s), 269
Gene conservation, 58-­61
Gene diversity, 154
Gene editing techniques, 251
Gene pool, 13, 26, 35, 58­61, 151­152, 314, 317­319, 324
Generalization, 35
Gene regulation, 35
Gene sharing, 18
Gene size, 66­67
Gene-targeted therapy, 19
Genetically engineered mouse (GEM), 233-­234
Genetic fine-tuning, 124­-138
Genetic heterogeneity, 130
Genetic instability, 79
Genetic mutations, 151
Genetic surplus disorder, 79
Genome, 12, 14-­15, 26, 35
Genome Wide Association Study (GWAS), 272
Genomic architecture, 64­73
Genomic disorder, 79
Genomic regulation, 76­87
Genomic regulatory processes, 125­138
Genomic regulatory systems, 
  pathologic conditions of, 121-­138
Genomic structural abnormalities (GSVs), 69
Genomic structural variation, 79
Germ cell, 6, 35
Germ cell line, 35­-36
Germ layers, 131
Germline, 79
Germline mutation, 80
Gestational trophoblastic disease, 234
Giant viruses, 162
Glires, 230
Globins, 13
Gnathostomata, 161, 214-­215
Gorillini, 232


H 
HACEK, 272
Haeckel's theory, 96-­97
Haemophilus influenzae, 244
Hair follicles, 223­224, 224f Hamartoma, 158, 166
Haploid, 7­8, 36
Haploid organisms, 7, 36
Haplorrhini/haplorhini, 231
Haplotype, 80
HAS2 gene, 248
Hemichordata, 197
Hepatitis B, 292
Hepatocyte, 100
Hepatoid adenomas, 119
Hepatoma, 131
Hereditary nonpolyposis colorectal cancer syndrome, 131
Heritability, 131
Heterokonts, 289, 301
Hirschspring disease, 209
Histone, 65, 199
Histone disruptors, mild effects of, 122
Histopathology, 131
Histozoa, 193
Hodgkin lymphoma, 273
Holometabolism, 156, 166
Holomycota, 186
Holozoa, 186
Holt-Oram syndrome, 123
Homeobox, 36
Hominidae, 231­232
Homininae, 232
Hominini, 232
Hominoidea, 231
Homo, 232
Homo erectus, 232
Homolog, 12, 18, 24, 36
Homologous genes, 316-­317
Homologous recombination, 
  during meiosis, 62
Homoplasy, 166
Homo sapiens, 147­149, 176, 232­235
Homozygosity, 80
Hookworms, 292
Horizontal gene transfer, 80
Horse, 
  gestation period of, 241f 
Horseshoe crabs, 149, 149f 
Host, 155­157, 159­161, 163, 166
HOX gene diseases, mild clinical course of, 123
HOX genes, 24
Human(s), 232­235
Human diseases, 115­118
Human embryo, dorsum of, 97f Human embryology, 246
Human embryonic stem cells, 100f Human gene pool, 55-­56
Human kidney, 101
Human phylogenetic lineage, 177­-179
Hutchinson-Gilford progeria syndrome, 263
Hydatidiform mole, 221, 234
Hydractinia carnea, 253
Hydrops-ectopic calcification-"moth-eaten" (HEM), 17-­18
Hylobatidae, 231
Hyperplasia, 273
Hypoxanthine-guanine phosphporibosyl transferase (HGPRT), 60­-61

Evolution’s Clinical Guidebook: Translating Ancient Genes Into Precision Medicine is available from Amazon or from the publisher's website. If you are fortunate enough to have full institutional access to ScienceDirect, you can download chapters at no cost.

Jules Berman

key words: evolution, precision medicine, genetics, rare disease, clinical genetics, bioinformatics, evo-devo, Jules J. Berman, Ph.D., M.D.

Contents: Evolution’s Clinical Guidebook: Translating Ancient Genes Into Precision Medicine

In yesterday's blog, I announced the publication of my book, Evolution’s Clinical Guidebook: Translating Ancient Genes Into Precision Medicine. The premise of this book is that modern medicine is based on an understanding of evolutionary processes. Basically, without evolution, the fledgling field of precision medicine would wither and die, and we would lose our opportunity to prevent, diagnose, and treat the diseases that account for the bulk of morbidity and mortality in humans and in animals.

This book is available from Amazon or from the publisher's website. If you are fortunate enough to have full institutional access to ScienceDirect, you can download chapters at no cost. Here is the Table of Contents.

Contents: Evolution’s Clinical Guidebook: Translating Ancient Genes into Precision Medicine

1. Evolution, From the Beginning 1

Section 1.1 In the Beginning 1
Section 1.2 Bootstrapping Paradoxes 5
Section 1.3 Our Genes, for the Most Part, 
Come From Ancestral Species 12
Section 1.4 How do Metabolic Pathways Evolve? 15
Section 1.5 Cambrian Explosion 21
Section 1.6 After the Cambrian: Coexistence 
and Coevolution 25
Glossary 29
References 44

2. Shaking Up the Genome 51
Section 2.1 Mutation Burden 51
Section 2.2 Gene Pools and Gene Conservation 58
Section 2.3 Recombination and Other 
Genetic Tricks 61
Section 2.4 Genomic Architecture: 
An Evolutionary Free-for-All 64
Section 2.5 Rummaging Through the DNA Junkyard 73
Glossary 77
References 87

3. Evolution and Embryonic Development 93
Section 3.1 The Tight Relationship Between 
Evolution and Embryology 93
Section 3.2 The Epigenome and the Evolution 
of Cell Types 103
Section 3.3 An Embryonic Detour for 
Human Diseases 115
Section 3.4 The Borderland of Embryology 
and Cancer 118
Section 3.5 Pathologic Conditions of the 
Genomic Regulatory Systems 121
Glossary 125
References 138

4. Speciation 145
Section 4.1 A Species is a Biological Entity 145
Section 4.2 The Biological Process of Speciation 147
Section 4.3 The Diversity of Living Organisms 152
Section 4.4 The Species Paradox 157
Section 4.5 Viruses and the Meaning of Life 159
Glossary 164
References 168

5. Phylogeny: Eukaryotes to Chordates 173
Section 5.1 On Classification 173
Section 5.2 The Complete Human 
Phylogenetic Lineage 177
Section 5.3 Eukaryotes to Obazoans 179
Section 5.4 Opisthokonts to Parahoxozoa 185
Section 5.5 Bilaterians to Chordates 193
Glossary 198
References 203

6. Phylogeny: Craniates to Humans 207
Section 6.1 Class Craniata and the Ascent 
of the Neural Crest 207
Section 6.2 Vertebrates to Synapsids 212
Section 6.3 Mammals to Therians 220
Section 6.4 Eutherians to Humans 226
Glossary 233
References 235

7. Trapped by Evolution 239
Section 7.1 Spandrels, Pendentives, Corbels, 
and Squinches 239
Section 7.2 Evolving Backwards 240
Section 7.3 Eugenics: Proceed With Caution 247
Section 7.4 The Evolution of Aging, 
and the Diseases Thereof 252
Section 7.5 Why Good People Get Bad Diseases 265
Glossary 270
References 277

8. Animal Models of Human Disease: Opportunities 
and Limitations 285
Section 8.1 The Animal Model Problem, in a 
Nutshell 285
Section 8.2 Specificities and Idiosyncrasies 286
Section 8.3 New Animal Options 294
Section 8.4 The Proper Study of Mankind 300
Glossary 301
References 302

9. Medical Proof of Evolution 307
Section 9.1 What Does Proof Mean, 
in the Biological Sciences? 307
Section 9.2 The Differences Between Designed 
Organisms and Evolved Organisms 309
Section 9.3 What if Evolution Were Just 
a Foolish Fantasy 316
Glossary 325
References 326
Index 329

Jules Berman

key words: evolution, precision medicine, genetics, rare disease, clinical genetics, bioinformatics, evo-devo, Jules J. Berman, Ph.D., M.D.

Just Published: Evolution’s Clinical Guidebook: Translating Ancient Genes Into Precision Medicine

This month, Academic Press has published my book, Evolution’s Clinical Guidebook: Translating Ancient Genes Into Precision Medicine. The premise of this book is that modern medicine is based, in one way or another, on an understanding of evolutionary processes. If evolution were a fabrication, then we would not be able to make any sense of the genomic data that is pouring out of research laboratories. We would not be able to design rational, cost effective, screening protocols to test the effectiveness of new drugs. We would not be able to identify the human sub-populations that will benefit from gene-targeted therapies. We would not be able to find the cause of rare diseases, and we would not be able to apply such knowledge to the treatment of common diseases. Without evolution, we would not understand how cancer develops, or how we might intervene in the process. Basically, without evolution, the fledgling field of precision medicine would wither and die, and we would lose our opportunity to prevent, diagnose, and treat the diseases that account for the bulk of morbidity and mortality in humans and in animals. This book demonstrates, through hundreds of examples, that modern medicine is built on the theory of evolution.

This book is available from Amazon or from the publisher's website. If you are fortunate enough to have full institutional access to ScienceDirect, you can download chapters at no cost.

Jules Berman

key words: evolution, precision medicine, genetics, rare disease, clinical genetics, bioinformatics, evo-devo, Jules J. Berman, Ph.D., M.D.

Genome-Specific Responses to Infection

A prior post listed 7 assertions regarding the role of infectious organisms on the human genome. In the next few blogs we'll look at each assertion, in excerpts from Precision Medicine and the Reinvention of Human Disease. Here's the third:

A good portion of the genes in humans (perhaps 10%) are involved in responses to infectious organisms.

It has been estimated that over 1000 human genes are involved in inflammation pathways [37]. Several studies have shown that following an inflammatory challenge or challenged by the introduction of a pathogen, more than a hundred genes are activated [38–40]. The activated genes include some of the same genes that have been associated with autoimmune diseases, suggesting that these disease-associated genes are conserved because they have a beneficial role, protecting us from invading pathogens [39]. The genetic profile of genes activated by inflammation is very similar from human to human, but quite dissimilar from the profile of genes activated by inflammation in the mouse [41]. This would suggest that species develop their own genome-wide responses to agents that cause inflammation (e.g., invading organisms).

- Jules Berman

key words: precision medicine, evolution, virus, viral, jules j berman Ph.D. M.D.

Vertebrate Evolution Driven by DNA from Infectious Organisms

A prior post listed 7 assertions regarding the role of infectious organisms on the human genome. In the next few blogs we'll look at each assertion, in excerpts from Precision Medicine and the Reinvention of Human Disease. Here's the second:

Some of the key steps in the development of vertebrate animals, and mammals in particular, have come from DNA acquired from infectious organisms.

The human genome has preserved its viral ballast, at some cost. At every cell division, energy is expended to replicate the genome, and the larger the genome, the more energy must be expended. Why do we spend a large portion of the energy required to replicate our genome, on inactive sequences, of viral origin? Why doesn’t our genome simply eject the extra DNA, a biological process that is commonplace in the evolution of obligate intracellular parasitic organisms? Maybe it's because we use viral genes to our own advantage.

Two evolutionary leaps, benefiting the ancestral classes of humans, and owed to the acquisition of viral genes, include the attainment of adaptive immunity and the development of the mammalian placenta. Let’s take a moment to see how these innovations came about.

Adaptive immunity evolved at about the same time that jawed vertebrates first appeared on earth. The crucial gene responsible for the great leap to adaptive immunity, the recombination activating gene (RAG), was stolen from a retrovirus. To understand the pivotal evolutionary role of RAG, we need to review a bit of high school biology. The adaptive immune system responds to the specific chemical properties of foreign antigens, such as those that appear on viruses and other infectious agents. Adaptive immunity is a system wherein somatic T cells and B cells are produced, each with a unique and characteristic immunoglobulin (in the case of B cells) or T-cell receptor (in the case of T cells). Through a complex presentation and selection system, a foreign antigen elicits the replication of a B cell whose unique immunoglobulin molecule (i.e., so-called antibodies) matches the antigen. Secretion of matching antibodies leads to the production of antigen-antibody complexes that may deactivate and clear circulating antibodies, or may lead to the destruction of the organism that carries the antigen (e.g., virus or bacteria).

To produce the many unique B and T cells, each with a uniquely rearranged segment of DNA that encodes specific immunoglobulins or T-cell receptors, recombination and hypermutation must take place within a specific gene region. This process yields on the order of a billion unique somatic genes, and requires the participation of recombination activating genes (RAGs). The acquisition of a recombination activating gene is presumed to be the key evolutionary event that led to the development of the adaptive immune system present in all jawed vertebrates (gnathostomes). Before the appearance of the jawed vertebrates, this sort of recombination was genetically unavailable to animals. Our genes simply were not equal to the task. Retroviruses, however, are specialists at cutting, moving, and mutating DNA. Is it any wonder that the startling evolutionary leap to adaptive immunity was acquired from retrotransposons? Thus,we owe our most important defense against infections to genetic material retrieved from the vast trove of retrovirally derived DNA carried in our genome [33]. As one might expect, inherited mutations in RAG genes are the root causes of several immune deficiency syndromes [34,35].

Many millions of years later, vertebrates acquired another gene that did much to enable the evolution of all mammals. Members of Class Mammalia are distinguished by the development of the placenta, an organ that grows within the uterine cavity (i.e., the endometrium). After birth, the placenta must detach from the uterus. You can imagine the delicate balancing act between attaching firmly to the wall of the uterus and detaching cleanly from the wall of the uterus. During placental development, large, flat cells called cytotrophoblasts form the interface between placenta and uterus. To create the thin membrane that borders the lining of the uterus and that borders the blood received from the uterus in the spaces between the placental villi, the cytotrophoblasts must somehow fuse into a syncytium (i.e., multinucleate collections of cells that have fused together by dissolving their individual cytoplasmic membranes).

There is one task at which all animals excel: maintaining a clear separation between one cell and another. In point of fact, the most distinctive difference between animal cells and all other cells of eukaryotic origin happens to be the presence of cell junctions, whose purpose is to bind cells to one another without fusing cells. This being the case, you can see that the normal direction of animal evolution would preclude the appearance of a gene intended to form a huge syncytium of placental cells. Whereas animal cells are failures at fusion, viruses are champions. One of the most often-deployed methods by which viruses invade cells is through fusion at the cytoplasmic membrane. It happens that retroviral envelope genes, preserved in the human genome, do a very good job at fusing membranes. Animals captured a retroviral fusogenic envelope gene and inserted it into one of the first syncytin molecules involved the development of the placenta. Apparently, this acquisition worked out so well for mammals that later-evolving mammalian classes made their own retrovirus gene acquisitions to obtain additional syncytins, thus refining the placenta for their own subclasses [23,36].

- Jules Berman

key words: precision medicine, evolution, virus, viral, jules j berman Ph.D. M.D.

RELIC DNA IN THE HUMAN GENOME

Yesterday's post listed 7 assertions regarding the role of infectious organisms on the human genome. In the next few blogs we'll look at each assertion, in excerpts from Precision Medicine and the Reinvention of Human Disease. Here's the first:

A significant portion of the human genome consists of relic DNA derived from ancient invasive organisms.

About 8% of our genome is derived from sequences with similarity to known infectious retroviruses, and these longer sequences can usually be recognized by their contained subsequences (e.g., gag, pol, and env genes) and long terminal repeats. The viral sequences in our genomes are the remnants of ancient retroviral infections, and the occasional nonretroviral infection, that were branded into DNA, and subsequently amplified [21–23]. Because much of the endogenous retroviral load in the human genome is due to amplification, and subsequent mutation, it is hard to determine the number of retroviral species that established their niche in the human gene pool, but studies of these viral remains would suggest that we contain species from several dozen families of retroviruses, with an undetermined number of contributions from individual family members [24]. Based on comparisons of the viruses present in different species of primates, it would appear that the most recent acquisition of an endogenous retrovirus occurred in humans between 100,000 and 1 million years ago [25]. Most of the retroviral sequences in our genomes are inactivated due to an accumulation of degenerative mutations collected over the eons, indicating that there has been little or no selective pressure to conserve retroviruses in their pristine sequences.

- Jules Berman

key words: precision medicine, human genome, evolution, infectious diseases, jules j berman, Ph.D., M.D.

Infections have made their mark on the Human Genome

In the context of Precision Medicine, infections draw our attention because they have played an important role in the evolution of the eukaryotic genome. Over the next few blog posts, we will explore the following:

• A significant portion of the human genome consists of relic DNA derived from ancient invasive organisms.
• Some of the key steps in the development of vertebrate animals, and mammals in particular, have come from DNA acquired from infectious organisms.
• A good portion of the genes in humans (perhaps 10%) are involved in responses to infectious organisms.
• Most of the cells in the human (at least 90%) consist of infectious organisms and commensals that have adapted to life within human hosts. [Glossary Commensal]
• Normal defenses can block every infectious disease. Hence, every infectious disease results from a failure of our normal defenses, immunologic and otherwise.
• Cellular defects that have no direct connection to immunity may increase susceptibility to infectious organisms.
• By dissecting the biological steps involved in the pathogenesis of infectious disease, it is possible to develop new treatments, other than antibiotics, that will be effective against a range of related organisms.

Over the next few blogs, we'll do our best to justify each of these (as yet) unproven assertions.

- Jules Berman

key words: precision medicine, infections, evolution, resistance to infection, jules j berman Ph.D., M.D.

The Importance of Biological Taxonomy

Biological taxonomy is the scientific field dealing with the classification of living organisms. Non-biologists who give any thought to taxonomy, may think that the field is the dullest of the sciences. To the uninitiated, there is little difference between the life of a taxonomist and the life of a stamp collector. Nothing could be further from the truth. Taxonomy has become the grand unifying theory of the biological sciences. Efforts to sequence the genomes of prokaryotic, eukaryotic and viral species, thereby comparing the genomes of different classes of organisms, have revitalized the field of evolutionary taxonomy (phylogenetics). The analysis of normal and abnormal homologous genes in related classes of organisms have inspired new disease treatments targeted against specific molecules and pathways characteristic of species or classes or organisms. Students who do not understand the principles of modern taxonomy have little chance of perceiving the connections between medicine, genetics, pharmacology, or pathology, to say nothing of clinical microbiology.

Here are two of the specific advantages of learning the taxonomy of infectious diseases.

1. As a method to drive down the complexity of medical microbiology

Learning all the infectious diseases of humans is an impossible task. As the number of chronically ill and immune-compromised patients has increased, so have the number of opportunistic pathogens. As global transportation has become commonplace, the number of exotic infections spread worldwide has also increased (See Glossary item, Exotic diseases in the United States). A few decades ago, infectious disease experts were expected to learn a few hundred infectious diseases. Today, there are over 1400 organisms that can cause diseases in humans, and the number is climbing rapidly, while the techniques to diagnose and treat these organisms are constantly improving. Textbooks cannot cover all these organisms in sufficient detail to provide healthcare workers with the expertise to provide adequate care to their patients.

How can any clinician learn all that is needed to provide competent care to patients? The first step in understanding infectious diseases is to understand the classification of pathogenic organisms. Every known disease-causing organisms has been assigned to one of 40 well-defined classes of organisms, and each class fits within a simple ancestral lineage. This means that every known pathogenic organism inherits certain properties from its ancestral classes and shares these properties with the other members of its own class. When you learn the class properties, along with some basic information about the infectious members of the classes, you gain a comprehensive understanding of medical microbiology.

2. As protection against professional obsolescence

There seems to be so much occurring the the biological sciences, it is just impossible to keep on top of things. With each passing day, you feel less in tune with modern science, and you wish you could return to a time when a few fundamental principles grounded your chosen discipline. You will be happy to learn that science is all about finding generalizations among data or among connected systems (i.e., reducing the complexity of data or finding simple explanations for systems of irreducible complexity). Much, if not all, of the perceived complexity of the biological sciences derives from the growing connections of once-separate disciplines: cell biology, ecology, evolution, climatology, molecular biology, pharmacology, genetics, computer sciences, paleontology, pathology, statistics, and so on. Scientists today must understand many different fields, and they must be willing and able to absorb additional disciplines, throughout their careers. As each field of science becomes entangled with other the seemingly arcane field of biological taxonomy has gained prominence because it occupies the intellectual core of virtually every biological field.

Modern biology is data-driven. A deluge of organism-based genomic, proteomic, metabolomic and other "omic" data is flooding our data banks and drowning our scientists. This data will have limited scientific value if we cannot find a way to generalize the data collected for each organism to the data collected in other organisms. Taxonomy is the scientific method that reveals how different organisms are related. Without taxonomy, data has no biological meaning.

The discoveries that scientists make in the future will come from questions that arise during the construction and refinement of biological taxonomy. In the case of infectious diseases, when we find a trait that informs us that what we thought was a single species is actually two species, it permits us to develop treatments optimized for each species, and to develop new methods to monitor and control the spread of both organisms. When we correctly group organisms within a common class, we can test and develop new drugs that are effective against all of the organisms within the class, particularly if those organisms are characterized by a molecule, pathway or trait that is specifically targeted by a drug. Terms used in diverse sciences, such as homology, metabolic pathway, target molecule, acquired resistance, developmental stage, cladistics, monophyly, model organism, class property, phylogeny, all derive their meaning and their utility from biological taxonomy. When you grasp the general organization of living organisms, you will understand how different scientific fields relate to each other, thus avoiding professional obsolescence.

- Jules Berman (copyrighted material)

key words: taxonomy, evolution, classification, data organization, jules j berman